China Wuhan Homsh Technology Co.,Ltd. Company News

      With its high accuracy and reliability, iris recognition technology has become a crucial component in the field of biometrics. In today’s era of growing demand for digital identity security, iris recognition technology, boasting high accuracy and reliability, is emerging as a vital part of the biometrics sector. Each individual’s iris texture is unique, featuring a high degree of distinctiveness and stability.       This technology captures iris images via a near-infrared camera, followed by the use of advanced algorithms for feature extraction and matching. Its false acceptance rate (FAR) can be as low as 1 in 1 million, far surpassing other biometric methods and providing unprecedented security guarantees for various industries. 1. Technical Principles and Advantages       Iris recognition is a biometric technology based on the textural features of the human iris. The iris is a circular, colored membrane located between the black pupil and the white sclera of the eye, and it ranks among the most unique biological features of the human body.       The iris recognition process consists of four key links: iris image acquisition, image preprocessing, feature extraction, and feature matching. Image preprocessing includes steps such as the localization of the inner and outer boundaries of the iris, normalization, image enhancement, and image denoising.       Compared with other biometric technologies, iris recognition has three core advantages:       High distinctiveness: Each person’s iris texture is unique—even identical twins have different iris patterns;       Lifelong stability: Iris textures form in infancy and remain nearly unchanged throughout a person’s lifetime;       Live detection capability: Iris recognition only works on living organisms, making it difficult to forge or replicate. 2. Hardware Equipment and Technological Evolution       Modern iris recognition devices comprise multiple core components, ranging from iris scanners to all-in-one iris recognition machines, which can meet the needs of different scenarios.       The optical imaging chain determines the final performance of the system. Mainstream solutions adopt safe near-infrared light as the light source—this light is imperceptible to the human eye and can avoid glare from visible light, ensuring clear iris images are obtained under different ambient light conditions.       Next-generation iris recognition technology continues to make breakthroughs in recognition distance, speed, and adaptability. Industrial-grade iris recognition devices can operate normally under a wide temperature range, satisfying the requirements of special environments. Outdoor devices support a high protection level, enabling them to adapt to various harsh weather conditions. 3. Software Algorithms and Integration Support       Iris recognition algorithms are constantly evolving—from traditional iris localization methods to deep learning-based feature extraction technologies—with continuous improvements in recognition accuracy and efficiency.       Compared with the original algorithms, the improved feature extraction algorithms have achieved a significant increase in the correct recognition rate. By optimizing and selecting feature points with high contrast and quality as the final iris feature vectors, these algorithms can reduce the false matching rate and improve the operational efficiency of the algorithms.       The iris recognition Software Development Kit (SDK) provides comprehensive development support, compatible with multiple programming languages and operating system platforms. The system supports 1:1 verification and 1:N search, enabling fast recognition even in databases with millions of entries. At the same time, the system offers a sound security protection mechanism, supporting advanced encryption algorithms and national cryptographic algorithms to ensure the security of biometric data. 4. Application Scenarios and Solutions       Iris recognition technology is widely applied across various industries. At airport border checkpoints and customs ports, iris recognition channels enable fast clearance; in financial institutions, iris recognition access control systems provide dual-authentication guarantees.       In the field of coal mine safety production, iris recognition technology provides effective technical support for access control management in key underground areas. By adopting a non-contact biometric authentication system, "person-specific control" management has been realized for critical locations such as underground substations and pump rooms. Leveraging the distinctiveness and stability of the iris, this system effectively solves the recognition problem caused by facial contamination of underground workers. Each authorized person can only enter the authorized area through iris verification within a specific time period, technically eliminating the risk of illegal entry by unauthorized personnel. Meanwhile, the system can also be connected to personnel positioning and alcohol detection systems, comprehensively improving the safety management level of underground operations and providing reliable support for the intelligent construction of coal mines.       In the field of public housing management, iris recognition technology has also been effectively applied. For example, Wuhan Homsh Technology Co., Ltd. once successfully implemented the "Iris Recognition Technology Integration Application Demonstration Project in Public Rental Housing Communities of Daxing District, Beijing", helping to solve common management problems in public rental housing such as subletting, illegal transfer, and fee arrears, and improving the level of technological management. 5. Security and Privacy Protection       As iris recognition technology is widely applied, security and privacy protection have become key considerations. Advanced iris security technologies can protect the security of iris information and prevent the leakage of biometric data.       Iris recognition systems adopt a variety of technical measures to ensure security. Live detection algorithms can effectively prevent spoofing methods such as photos and videos, ensuring the security and reliability of the recognition process. Generally, the system does not store the iris images themselves, but rather encrypted feature templates—even if data is leaked, the original iris information cannot be restored.       Multimodal biometric technology has become a development trend. By integrating multiple biometric authentications and dynamic anti-counterfeiting technologies, a full-link security protection system from the device end to the business system can be built, meeting the needs of high-security-level scenarios. 6. Future Development Trends and Challenges       Iris recognition technology is moving toward greater intelligence and integration. AI-based iris recognition algorithms continue to improve recognition accuracy and speed, while 5G technology opens up new possibilities for remote iris recognition. The application of edge computing technology makes iris recognition devices more intelligent, supporting localized processing and data protection.       Multimodal fusion has become an important trend. Solutions integrating multiple biometric recognition technologies—by combining biometric data collection, a trusted authentication platform, and business systems—have been implemented in some government service centers, helping to improve work efficiency.       Cost reduction and technological popularization are driving the continuous expansion of the application scope of iris recognition. Supply chain optimization has significantly reduced the cost of iris modules, supporting the wider promotion of the technology. Technological development also covers anti-interference algorithms for more complex environments, expanding the geographical scope of application. Important progress has also been made in standardization and compliance. With the formulation and improvement of relevant national standards, the standardized development of the industry has received strong support. Iris recognition algorithms have passed testing and certification by authoritative institutions, providing official endorsement for technological promotion.       In the future, with the in-depth integration of artificial intelligence, 5G, and edge computing technologies, iris recognition technology will embrace broader development prospects. As a leading domestic provider of iris biometric technology, Wuhan Homsh Technology Co., Ltd. has always been committed to the R&D and innovation of core iris recognition algorithms and owns complete independent intellectual property rights. The company will continue to promote the upgrading and implementation of multimodal biometric systems. By deeply integrating multi-dimensional feature recognition technologies such as iris and facial recognition, it will provide overall identity authentication solutions with higher security levels and better user experience for industries including finance, security, and intelligent transportation—truly empowering thousands of industries with cutting-edge biometric technology and jointly creating a safe and convenient intelligent future.

      Scenes in sci-fi movies where confidential access is granted via eye scanning have now become real-life security solutions. Iris recognition technology is no longer confined to laboratory environments; instead, it serves as a mature security measure, widely applied in various fields around us. Understanding Iris Recognition Devices: Sophisticated Security Guardians      An iris recognition device is a precision system that integrates optics, electronics, and artificial intelligence (AI) technologies. While its appearance varies by application scenario, it internally contains core modules specifically designed to achieve accurate and secure identification. Core Technical Components:      The Optical Acquisition Module adopts dedicated near-infrared (NIR) cameras and infrared LED illumination units. Near-infrared cameras are specialized in capturing the detailed texture of the iris under specific spectral illumination—this light is safe and invisible to the human eye, enabling clear capture of the iris’s unique features. The infrared LED illumination units ensure stable image quality under all lighting conditions.      The Intelligent Processing Module is equipped with a high-performance processor and advanced algorithms. It can complete complex computing processes such as eye localization, image quality optimization, and feature extraction within milliseconds, ultimately generating a unique digital feature code.      The Interactive Feedback System provides users with intuitive operation guidance and recognition result feedback through multi-color LED indicators and audio prompts, ensuring a smooth and natural user experience.      Iris recognition devices come in diverse forms, including micro-modules integrable into mobile devices, embedded devices for access control systems, and specialized large-scale devices for high-security locations—all tailored to meet the needs of different scenarios. An Analysis of Professional Usage Processes Phase 1: Image Acquisition and Liveness Detection      The user needs to stand within the optimal recognition distance of 30–50 centimeters in front of the device. The system activates safe near-infrared illumination while running liveness detection algorithms to ensure the captured object is a real biological feature. The device automatically optimizes acquisition parameters to ensure iris images that meet identification requirements are obtained under varying environmental conditions. Phase 2: Eye Localization and Feature Extraction      Intelligent recognition algorithms accurately lock onto the eye area and automatically handle interference factors such as eyelash occlusion and lens glare. The system performs standardization and quality enhancement on the captured images, uses deep learning algorithms to extract feature information from the iris texture, and converts it into a digital feature template. Phase 3: Feature Matching and Identity Verification      The system rapidly compares the real-time generated feature template with pre-registered templates, calculating the matching degree via pattern recognition algorithms. The entire process uses encryption technology to ensure data security; verification results are returned in an extremely short time, and the system feeds back the recognition status to the user through visual or auditory means. Practical Application Scenarios Government Agencies and Immigration Checkpoints      Immigration authorities in multiple countries have adopted iris recognition technology to improve customs clearance efficiency. Major international airports are equipped with iris passage devices—registered passengers can quickly complete identity verification through dedicated channels, significantly reducing waiting times. Financial Institutions and Data Centers      Critical facilities such as bank vaults and data centers generally use iris access control systems. These devices are installed at key entry points and integrated with access control systems; staff must use both their employee ID cards and pass iris verification (a two-factor authentication process) to gain entry permission. Research and Medical Institutions      Iris recognition devices are used to manage access rights in areas such as research laboratories, pharmaceutical storage facilities, and medical archives. This ensures that only authorized personnel can access sensitive materials and information, effectively safeguarding research data and patient privacy. Outlook on Application Prospects      As technology continues to advance and costs gradually decrease, iris recognition devices are expanding into more application fields.      Smart home systems may integrate iris recognition functions to enable keyless entry and personalized environment settings—adjusting living conditions automatically based on the identified family member.      Educational institutions can apply iris recognition technology to manage dormitory access, library book loans, and exam identity verification, enhancing both management efficiency and security.      The automotive sector is expected to introduce iris recognition technology to implement personalized intelligent cockpit systems and enhance vehicle security systems, bringing drivers a safer, more convenient, and personalized travel experience.      From professional fields to daily life, iris recognition technology is redefining the way identity verification works. When we see these devices in operation, they are leveraging each individual’s unique biological features to provide safer and more convenient services. With technological progress and widespread application, we are moving toward an increasingly intelligent future.

      In today’s era of rapidly advancing biometric technology, Homsh Technology has reached a significant milestone — we have successfully submitted the company’s first patent application for an AI-based iris algorithm. Titled "An Iris Segmentation Method Based on an Improved UNet Model", this patent marks a solid step forward for Hongshi Technology in the in-depth integration of artificial intelligence (AI) and biometrics.       Iris recognition is hailed as the crown jewel of biometric technology. Its uniqueness and stability make it highly favored in high-security scenarios. However, achieving accurate iris region segmentation in complex environments has long been a technical challenge for the industry. Practical challenges such as varying lighting conditions, eyelid occlusion, and motion blur have all tested the robustness of algorithms. After in-depth research, Homsh Technology’s R&D team innovatively combined deep learning technology with iris recognition to create this groundbreaking solution.       The core innovation of this patent lies in the in-depth transformation of the classic UNet network architecture. The R&D team ingeniously adopted MobileNetV3 as the backbone network for feature extraction and integrated the CBAM (Convolutional Block Attention Module) attention mechanism, enabling the algorithm to automatically focus on the key features of the iris. Meanwhile, by introducing the ASPP (Atrous Spatial Pyramid Pooling) multi-scale dilated convolution module, the algorithm can better capture the global contextual information of images, significantly improving the segmentation accuracy of iris boundaries.       More notably, this patent also innovatively integrates dual-band liveness detection technology. Through the coordinated collection of two near-infrared bands (810nm and 940nm), the system can leverage the difference in hemoglobin absorption across different bands to effectively distinguish between real human eyes and spoofing attacks such as photos and videos. This design not only enhances the accuracy of iris recognition but, more importantly, improves its security. Test data shows that the system’s false acceptance rate (FAR) and false rejection rate (FRR) have been significantly optimized, fully meeting the strict requirements of the ISO 19794-6 international standard.       In terms of technical implementation, the R&D team also fully considered the needs of practical applications. By adopting advanced optimization strategies such as mixed-precision training and cosine annealing learning rate scheduling, they not only accelerated the model training process but also significantly improved the algorithm’s generalization ability. The system supports ONNX format conversion and can be flexibly deployed on various hardware platforms, truly achieving a seamless transition from laboratory research to industrial application.       The submission of this patent not only demonstrates Homsh Technology’s technical strength in AI algorithm R&D but also highlights the company’s determination to pursue continuous innovation in the field of iris recognition. From traditional image processing methods to the full application of deep learning technology, and from a single recognition function to comprehensive security protection integrated with liveness detection, Homsh Technology is driving technological progress across the entire industry through concrete actions.       Looking ahead, Homsh Technology will continue to deepen its research in iris recognition technology. Taking this patent as a starting point, we will constantly explore new frontiers in the integration of AI and biometric technology. We believe that through sustained technological innovation and the accumulation of intellectual property rights, Homsh Technology will surely deliver safer and more convenient identity authentication experiences to users in broader application scenarios such as intelligent security, financial payment, and smart cities.       The submission of this patent is not only an important milestone in Homsh Technology’s development journey but also a new starting point for us to move toward our vision of "becoming a world-leading provider of iris recognition technology". We would like to thank every partner for their trust and support. Homsh Technology will continue to be driven by innovation, safeguard security with technology, and make identification smarter.

      The in-depth integration of artificial intelligence (AI) technology and iris recognition is bringing revolutionary changes to the automotive industry. This combination not only enhances the security protection level of vehicles but also redefines the intelligent human-vehicle interaction experience. Technical Advantages of Iris Recognition   Iris recognition technology has unique advantages in the field of biometric recognition, making it an ideal choice for intelligent automotive safety:         The iris possesses a high degree of uniqueness. Each person's iris texture structure is unique, and scientific research has confirmed that the iris contains rich feature information, providing a reliable foundation for biometric authentication.         Iris features remain stable over the long term. Once fully developed, iris textures remain essentially unchanged with age or environmental variations. This characteristic makes it highly suitable as a long-term vehicle identity verification method.         Additionally, iris recognition has excellent anti-counterfeiting performance. The complex texture structure of the iris is difficult to replicate or forge. When combined with AI algorithms, the system can effectively identify liveness features, offering stronger anti-counterfeiting capabilities.   How AI Enhances Iris Recognition Performance   The application of AI technology has significantly improved the overall performance of iris recognition systems:         Intelligent image processing technology, based on deep learning algorithms, can automatically optimize captured iris images, including functions such as noise reduction and contrast enhancement. Even when light conditions change during driving or the user moves slightly, the system can still obtain high-quality iris images.         In terms of feature extraction, AI algorithms can automatically identify effective features from iris images, avoiding the limitations of manual feature design in traditional methods. Through extensive data training and algorithm optimization, deep learning models continue to improve recognition accuracy and processing speed.         The system also exhibits strong adaptability. AI algorithms can effectively handle image variations caused by factors such as lighting conditions, natural pupil dilation/constriction, or angle differences between the user and the camera, ensuring a consistently reliable authentication experience.   Innovative Applications in the Automotive Field   In the automotive industry, AI-driven iris recognition technology is demonstrating its value in multiple aspects:         By authenticating the driver's identity through iris recognition, the system can automatically retrieve preset personalized configurations, including seat position, steering wheel settings, rearview mirror angles, and air conditioning preferences. This technology already has feasible implementation plans, providing users with an "immediately usable upon boarding" intelligent experience.         Iris recognition technology can serve as an identity verification method before vehicle startup, enhancing the vehicle's security protection level. Related technologies have obtained patent protection, offering new solutions to prevent unauthorized use.         Existing technical solutions can implement iris recognition using in-vehicle cameras, supporting scenarios such as in-car payments and identity verification for in-vehicle applications. Users can complete security authentication without additional operations, greatly improving usability.         Current driver monitoring systems typically use cameras to monitor driver status. Iris recognition technology focuses primarily on the field of identity authentication, and its high-precision characteristics provide possibilities for integrating more biometric applications in the future.   Technical Implementation and Challenges   Integrating iris recognition technology into the automotive environment requires addressing several technical challenges:         Environmental adaptability is a primary consideration. Lighting conditions inside vehicles vary widely, ranging from intense sunlight to dim environments. Through advanced image processing technologies, AI algorithms can adapt to these changes, ensuring stable operation under all conditions.         Dynamic recognition capability is equally important. Vibrations during vehicle operation and minor movements of the driver are technical difficulties in implementation. Through image stabilization technology and prediction algorithms, the system can compensate for these movements, ensuring recognition accuracy.         Real-time response requirements cannot be ignored. Automotive applications have high demands for system response speed. With edge computing and optimized algorithms, modern iris recognition systems can complete identity verification in an extremely short time, meeting the needs of real-time applications.         Data privacy and security protection are crucial. As sensitive biometric information, iris data requires processing using advanced encryption technologies. After capturing iris images, the system immediately performs feature extraction and cryptographic processing to generate irreversible feature values, essentially protecting original biological information.   Future Outlook   As technology continues to advance, the application of AI and iris recognition in the automotive field will further expand:         Multimodal fusion systems are a future development direction. Vehicles may combine multiple biometric features to build multi-level identity verification systems, providing more comprehensive security. Such fusion systems can select the most appropriate authentication method based on different environmental conditions, ensuring the reliability of the authentication process.         Integration with intelligent transportation systems is also promising. Iris recognition technology may combine with urban intelligent transportation systems to achieve full-process automation from vehicle access to transportation fee payment, creating a more convenient urban travel experience.         Health monitoring functions may be a future expansion direction. Studies have shown that iris features are associated with certain health conditions. In the future, vehicles may provide basic health monitoring services through iris scanning, offering valuable health references to drivers.         Personalized autonomous driving experiences will also benefit from iris recognition technology. With the development of autonomous driving technology, iris recognition can support personalized settings and security controls for vehicles, providing each user with a customized autonomous driving experience.         The combination of AI and iris recognition technology is bringing new development opportunities to the automotive industry. By enhancing security, personalization, and convenience, it is improving the way users interact with vehicles. As technology continues to mature, this advanced technology is gradually becoming an important component of modern vehicles, offering users a more intelligent and secure driving experience.

      In the digital age, identity security faces unprecedented challenges. With the continuous development of technology, identity authentication has evolved from passwords to fingerprints and facial recognition. Now, iris recognition technology is becoming the "highest security gateway" for digital security with its unparalleled security. This article will delve into the background logic, application scenarios, technical mechanisms, and risk countermeasures of AI + iris technology, helping you fully understand how this cutting-edge technology safeguards our digital security and how it will reshape our future lives. Background Logic: Why "AI + Iris"? The Evolution of Identity Security      Digital identity security has undergone a long evolution from passwords to biometrics. In this process, we have witnessed the transformation from "something you know" (passwords) to "something you have" (fingerprints, facial features). As the "crown jewel" of biometrics, the iris has three unrivaled advantages:       Uniqueness: Each person's iris texture is unique, even among identical twins.Stability: Iris texture forms a few months after birth and remains stable for life, without changing with age.      Unreplicability: The complex texture of the iris is almost impossible to perfectly replicate, far exceeding the security of fingerprints and facial features.       These characteristics make the iris recognized as the "highest level" biometric, especially suitable for high-security identity authentication scenarios. The Necessity of AI Empowerment             The integration of AI technology has significantly improved the robustness of iris recognition, enabling high accuracy even under non-ideal conditions. For example, in low-light environments or when users wear glasses, AI models can still accurately extract iris features and complete identity verification. This improvement has made it possible for iris recognition technology to move from laboratories to large-scale commercial use, bringing revolutionary changes to digital security in various industries. A Comprehensive Analysis of AI + Iris Application Scenarios       AI + iris technology is not just a security technology, but also a revolution in digital life. From financial payments to smart terminals, from urban security to healthcare, and to the future network, this technology is reshaping the way we interact with the digital world. Financial Security (Banking, Payments)      Current Situation: The popularity of mobile payments has increased the risk of account theft.      Iris Value: Harder to forge than facial features, effectively preventing "photo attacks/video attacks".      AI + Iris Solution: Integrating deepfake detection and liveness detection technologies to ensure a trusted payment environment, providing "impregnable" protection for digital asset transactions.Smart Terminals (Mobile Phones, PCs, XR)      Trend: Next-generation high-end smart devices will generally integrate iris recognition modules.      AI Empowerment: Maintaining high recognition accuracy even with small-sized sensors and complex lighting conditions.      Security Scenarios: Encryption of sensitive data, protection of corporate secrets, identity authentication for remote work, creating a "portable digital safe" for users.Smart Cities and Access Control Systems      Pain Point: The accuracy of facial recognition drops significantly in mask-wearing environments or low-light conditions.      Iris Advantage: Unaffected by mask coverage,stable operation in various environments.      AI Capability: Rapid positioning of the eye area + precise iris segmentation, ensuring a fast passage experience under high concurrent pedestrian flow.Healthcare      Trend: The iris is not only an identity credential but also a "biological window" reflecting health status.      Dual Value: AI can not only identify identities but also analyze indicators related to iris texture and fundus health.      Future Application: Combining with smart hardware to realize the innovative service model of "one iris collection = identity verification + health early warning".Future Networks (Web3, Metaverse)      Identity Dilemma: The secure mapping between digital identity and real identity is       related to the basic security of the virtual world.      Iris Value: A more trustworthy biometric authentication method than blockchain wallets.      AI Expansion: Iris + encrypted computing to realize zero-knowledge proof-based identity authentication, proving "who I am" without exposing personal data.       In these application scenarios, AI + iris technology not only provides a higher level of security but also creates a new user experience. With the maturity of technology and the reduction of costs, we can foresee that in the next 3-5 years, iris recognition will gradually penetrate into all aspects of daily life from high-end security fields, becoming the "security cornerstone" of the digital world. Technical Mechanism: Revealing the Working Principle of AI + Iris       To help readers without a technical background understand the core working principle of AI + iris technology, we simplify the complex technical process into four key steps. These steps show the complete process from iris image acquisition to final identity verification, and the key role played by AI technology in each link.Iris Image Acquisition      A near-infrared (NIR) camera is used to capture iris texture. Near-infrared light can penetrate the cornea, clearly display the fine texture of the iris, and cause no harm to the eyes. AI algorithms will real-time evaluate image quality to ensure that the captured iris images meet the recognition standards.AI Image PreprocessingComputer vision models based on deep learning complete a series of key tasks:       Precisely locate the eye area      Accurately segment the pupil boundary and iris outer edge      Compensate for light changes and perspective deviations      Filter out interference factors such as eyelashes and eyelidsDeep Feature Extraction      Advanced neural network architectures such as Vision Transformer (ViT) are used to extract high-dimensional feature vectors from iris textures. These features have:       High discriminability: Can accurately distinguish different individuals      Good stability: Features of the same individual are similar under different conditions      Strong anti-interference ability: Insensitive to changes in light, angle, etc.Feature Comparison and Judgment      The system compares the extracted feature vectors with the templates stored in the database and calculates the similarity score (usually using cosine similarity or Hamming distance). Based on the preset threshold, the system makes the final "accept" or "reject" judgment. Advanced systems also combine liveness detection results to prevent forgery attacks. How AI Improves the Performance of Iris Recognition       As shown in the figure above, AI technology has significantly improved various key performance indicators of iris recognition. Especially in anti-interference ability and liveness detection, AI-empowered systems have improved performance by more than 30% compared with traditional technologies, which directly determines the reliability and security of the technology in practical applications.       It is worth mentioning that with the development of edge computing technology, these complex AI algorithms can already run efficiently on mobile devices and IoT devices without relying on cloud computing, thus ensuring local processing of private data and fast response capabilities. This change in computing paradigm has truly made AI + iris technology ready for large-scale commercial use. Risks and Countermeasures: Building a Sustainable Iris Recognition Ecosystem       Although AI + iris technology has great potential, we must objectively recognize its challenges and risks and propose corresponding solutions to ensure the healthy and sustainable development of this technology.Main Risks      Data Security Risks: As a lifelong stable biometric feature, once iris data is leaked, it will cause irreversible security risks. Unlike passwords, users cannot "change" their irises.      Device Popularization Challenges: Currently, the cost of iris collection devices is relatively high, especially high-precision near-infrared cameras, which are much more expensive than fingerprint sensors, limiting the large-scale application of the technology.      User Privacy Concerns: Many users worry that iris scanning will collect health information or conduct excessive monitoring, and this psychological barrier affects the acceptance of the technology.      Technology Abuse Risks: Without effective supervision, iris recognition technology may be used for unauthorized identity tracking or scenarios against users' wishes.Countermeasures      Encryption and Decentralization: Adopt advanced cryptographic technologies such as homomorphic encryption and zero-knowledge proof to protect iris data; realize secure training with "data not leaving the local" through federated learning; build a decentralized identity authentication system using blockchain technology.      Localization and Scale Effect: Promote the localized research and development of iris collection modules, reduce hardware costs through scale effects and supply chain integration; explore the possibility of reusing existing camera modules for iris collection to reduce additional hardware investment.      Transparency and User Empowerment: Improve technical transparency, clearly inform users of data usage and protection measures; emphasize the dual value of iris recognition (security + health); allow users to fully control the authorization and usage scope of their iris data.      Ethical Guidelines and Regulations: Establish strict industry ethical guidelines and technical specifications; promote legislation to protect biometric data; require all iris recognition applications to obtain clear user informed consent. Future Outlook: The Development Path of AI + Iris       AI + iris is the "highest security gateway" for digital security in the next 20 years. It not only protects your assets and information but may also protect your health in the near future.       With the continuous maturity of technology and the continuous reduction of costs, we have reason to believe that AI + iris technology will gradually penetrate into all aspects of daily life from specific high-security scenarios within 5-10 years. It will not only become a solid barrier for digital security but also, with its convenience and versatility, become an important bridge connecting the physical world and the digital world.       As witnesses and participants in this technological wave, we should not only maintain enthusiasm for technological innovation but also adhere to the bottom line of ethics and security, and jointly build a safer, more convenient, and more humanized digital future.       Homsh Technology is committed to creating China's leading AI + iris recognition solutions, providing high-security identity authentication services for finance, medical care, smart terminals, and other fields. For more information or business cooperation, please pay attention to our official website or contact our technical team.

      As a core underpinning for identity verification and security protection in the digital age, biometric technology has been deeply integrated into various sectors of social production and daily life. Among its branches, iris recognition technology—bolstered by the inherent uniqueness and lifelong stability of iris textures—is emerging as one of the fastest-growing segments in this field. Driven by ongoing demands in security upgrading, financial risk control, and public services, iris recognition not only addresses the shortcomings of traditional methods (e.g., password vulnerability and physical card loss) but also demonstrates outstanding technical advantages. As a key branch of the biometric technology system, iris recognition, with its "exceptional accuracy and security," is expanding from high-security scenarios to broader civilian applications, thereby garnering significant attention from policymakers, the market, and users alike. I. Explosive Market Growth      The iris recognition market is experiencing a period of rapid expansion. In 2020, the global shipment volume of enterprise-grade iris recognition terminals reached nearly 60 million units, corresponding to a market size of approximately USD 1.35 billion. By 2023, the global sales volume of iris recognition devices had grown to RMB 6.2 billion (about USD 900 million), with enterprise-grade terminal shipments exceeding 100 million units—representing a compound annual growth rate (CAGR) of 22% from 2020 to 2023. In 2024, the global market size further climbed to USD 5.34 billion, and it is projected to reach USD 13.87 billion by 2030, maintaining a steady CAGR of 17.2% over the next six years, underscoring strong long-term growth momentum.      This growth is fueled by multiple factors, including policy support, reduced costs of 3D acquisition equipment (facilitating technology popularization), improved technical accuracy, higher penetration of multi-modal fusion solutions in financial security scenarios, and the continuous expansion of application scenarios. II. Technological Innovation Breakthroughs by Homsh      Founded in 2011, Homsh (Wuhan Homsh Technology Co., Ltd.) is a high-tech enterprise with fully independent intellectual property rights in core iris recognition algorithms. The company has achieved significant technological breakthroughs in the field of iris recognition, successfully developing a high-efficiency iris segmentation model based on deep learning. Adopting an advanced neural network architecture, this model leads the industry in both accuracy and processing speed, with a Dice coefficient exceeding 0.97 and an Intersection over Union (IoU) exceeding 0.94.      Homsh’s newly launched OVAI Iris Recognition System features an end-to-end optimized design, innovatively integrating preprocessing, segmentation, and recognition steps. The system incorporates multi-level intelligent segmentation technology, which enhances segmentation accuracy in complex scenarios through three phases: coarse segmentation, fine segmentation, and detailed segmentation. Additionally, it introduces the CBAM (Convolutional Block Attention Module) dual attention mechanism, optimizing feature extraction from both channel and spatial attention dimensions to achieve more precise iris localization and feature extraction.      Homsh has also successfully filed two invention patents representing major technological breakthroughs: "Pupil Boundary Detection Method and System Based on Multi-Algorithm Fusion" and "Iris Image Quality Assessment Method and System".      The multi-algorithm fusion pupil boundary detection technology adopts an innovative three-stage algorithm architecture: first, Hough circle transform is used for initial localization; second, adaptive thresholding and contour detection enable precise localization; and finally, fixed thresholding and morphological operations complete boundary optimization. The system also innovatively incorporates a biological feature verification mechanism, which validates results based on the biological characteristics of the pupil, effectively eliminating false detections and significantly improving detection accuracy under complex lighting conditions.      The iris image quality assessment system establishes a multi-dimensional evaluation framework, encompassing key technologies such as Weber contrast assessment, entropy-based grayscale utilization analysis, and intelligent eyelid/eyelash detection. Innovatively, the system adopts an adjustable weight scoring mechanism, which dynamically adjusts the weight ratio of various quality indicators according to the requirements of different application scenarios to achieve personalized assessment.      These two patented technologies complement each other, jointly addressing key challenges in image acquisition and quality control for iris recognition systems. Through multi-algorithm collaboration and intelligent quality assessment, they significantly enhance the adaptability and reliability of iris recognition systems in complex environments, providing technical support for high-end application scenarios such as financial payments and security access control, and advancing the large-scale commercialization of iris recognition technology. III. Diversified Expansion of Application Scenarios      Iris recognition technology is expanding from traditional security fields to a wider range of application scenarios.      In the field of access control, iris recognition has become a standard configuration for high-security areas. Compared with traditional access control systems, iris access control systems only require eye information collection, offering advantages such as uniqueness, stability, and anti-counterfeiting, which effectively enhance security.      In the intelligent automotive sector, iris recognition is emerging as an innovative feature in high-end vehicle models. Via vehicle-mounted infrared cameras, drivers can "unlock and start the vehicle with their eyes"; the system also automatically adjusts personalized settings such as seats and rearview mirrors. Meanwhile, iris recognition enables hierarchical management of driving permissions and provides millisecond-level security verification for scenarios such as in-vehicle payments and application authorization, ensuring vehicle security without the need for physical keys.      Iris recognition technology is also applied in areas such as smartphones, payment devices, and medical equipment. With the advent of the Internet of Things (IoT) era, the security demands of intelligent devices continue to rise, making high-security iris recognition a key focus of technology development for manufacturers. About Homsh      As a technology leader deeply engaged in the iris recognition field, Homsh (Wuhan Homsh Technology Co., Ltd.) will continue to take technological innovation as its core driving force, focusing on the iris recognition and biometric identification track to create safer, more convenient, and reliable recognition solutions for users. In the future, the company will further increase R&D investment, explore in-depth synergy between iris recognition and cutting-edge technologies such as artificial intelligence (AI), big data, and cloud computing, promote the penetration of biometric technology into more scenarios, and inject greater momentum into the security construction of the digital society.

      With the rapid development of digital payments and intelligent finance today, the security and convenience of identity authentication have become core demands of the industry. Boasting an optimized false acceptance rate (FAR) of one in ten million (0.0001%), iris recognition technology is gradually emerging as the preferred solution for high-security scenarios in the financial sector. From access control management for bank vaults to cardless transactions on self-service devices, this technology—hailed as the "crown jewel of biometrics"—is reshaping the landscape of financial security.       Identity authentication in the financial field has long been plagued by risks such as counterfeit card fraud and password leaks. Traditional magnetic stripe card authentication offers extremely low security, while chip cards, though more secure, still face the risk of duplication.                 Password-based authentication, on the other hand, is prone to issues like forgetting or theft. The introduction of iris recognition technology has fundamentally changed this situation: each person’s unique iris texture serves as an irreplicable "living password," and when combined with liveness detection technology, it can effectively fend off spoofing attacks using photos, videos, and other means.       In bank internal control scenarios, iris recognition has become a standard feature in high-security areas. By linking with employee permission databases, it achieves precise matching of "person, position, and authority." Cross-industry practices show that after the adoption of biometric technology, the audit efficiency of high-security areas can be improved by over 40%, and incidents of unauthorized internal access have decreased significantly. This technological empowerment not only strengthens security management but also optimizes the cost structure of management through automated processes.       Self-service financial devices have become a key application area for iris recognition. Some banks have piloted iris-recognition ATMs, which enable cardless operations and significantly enhance user experience. The application of biometric technology has reduced ATM fraud risks by 40%, fundamentally eliminating the hidden danger of card theft. Particularly in inclusive finance scenarios, this authentication method—no need to remember passwords and unaffected by hand conditions—effectively addresses barriers to financial services for special groups.       Financial-grade iris recognition solutions often adopt a multimodal fusion strategy. Recognition engines that combine iris with other biometrics (such as fingerprints and facial features) can further reduce the false acceptance rate in complex environments like strong light or backlighting through intelligent feature complementarity. This technology combination not only retains the high security of iris recognition but also improves adaptability in complex scenarios via multi-feature complementation. Currently, it has been piloted in intelligent counters of many banks.       Iris payment is transitioning from a concept to pilot applications. Users can complete "frictionless payments" in virtual scenarios through millisecond-level iris authentication. The core algorithm of payment terminals with iris verification functions has been tested to have a false acceptance rate as low as one in ten million. Users only need to register their iris information and bind it to their accounts; during consumption, they can complete payments by scanning their irises with the terminal—no need to carry a mobile phone or card throughout the process. This frictionless payment method not only improves transaction efficiency but also builds a multi-level security protection system.       With technological maturity and cost reduction, the application boundaries of iris recognition in the financial sector are constantly expanding. According to data from the 2025 Iris Recognition Market Report, the scale of China’s iris recognition market reached 10.39 billion yuan (RMB) in 2024, with significant growth in applications in the financial field. From core banking systems to third-party payment platforms, iris recognition is building a comprehensive financial security network.       Fintech experts point out that the integration of iris recognition with technologies such as blockchain and privacy-preserving computation is expected to open up new development horizons. In the future, iris recognition systems using federated learning technology can complete model training without sharing raw data, solving the problem of data silos in cross-institutional identity verification. With the promotion of central bank digital currency (CBDC), iris recognition is also expected to become an important identity anchor for the digital yuan, providing "technology + system" dual security guarantees for financial transactions.       From physical branches to virtual spaces, iris recognition technology is building an invisible shield for financial security. It is not only a technological innovation but also represents the leap of financial services from the "card and certificate era" to the "biometric era." In this balancing act between security and convenience, iris recognition undoubtedly provides an optimal solution for the financial industry. Its development and maturity will continue to drive financial services toward greater security and intelligence.

I. The Iris Observation System in TCM Ocular Diagnosis       The theoretical foundation of TCM Iridodiagnosis can be traced back to the record in Huangdi Neijing (Inner Canon of the Yellow Emperor) - Lingshu (Miraculous Pivot) - Chapter on Great Perplexity, which states that "the essence of the five zang-organs and six fu-organs ascends and infuses into the eyes". This theory of correlation has long clarified the close connection between the zang-fu organs and the eyes. Modern clinical studies have found that changes in iris texture may be associated with certain physical conditions. Currently, some domestic institutions and research institutes are exploring the integration and innovation of iris imaging technology with TCM natural rehabilitation medicine, aiming to provide references for health management through iris feature analysis. II. Cross-Temporal Resonance Between Divination Traditions and Modern Technology      In the 19th century, a Hungarian scientist created the first anatomically accurate map of the human iris, systematically documenting the classification of iris textures and proposing naming conventions such as "radial lines" and "pit-like patterns". This system was referred to as "ocular diagnosis", which is what we now call iridodiagnosis.      The early observations of iris textures share structural similarities with the Daugman Algorithm used in modern iris recognition technology—their commonality lies in focusing on the topological features of iris folds. Modern technology has significantly improved the accuracy of iris recognition by leveraging near-infrared imaging and live detection (e.g., dynamic pupil verification). In contrast, the error margin of iris observation was much larger in the early era when records relied on hand-drawing. This technological evolution clearly demonstrates that humanity’s approach to "decoding" the iris is shifting from subjective speculation in the past to an objective and quantitative scientific path. III. Cultural Differences and Technology Acceptance      The differences in the acceptance of iris recognition essentially stem from cultural conflicts in the "view of the body":      In the East Asian cultural context, the eyes have always been endowed with the special significance of a "gateway to the spirit". The ethical tradition of "do not look at what is not in accordance with ritual propriety" (from the Book of Rites) has long deeply linked ocular perception to an individual’s moral boundaries and spiritual privacy. This cultural perception means that people’s wariness toward ocular information collection is essentially a defense of the "privacy boundary in the visual domain". From an East Asian cultural perspective, ocular data is not only biological information but also a symbol carrying an individual’s spiritual traits. Therefore, concerns about its unauthorized use originate from the adherence to the cultural tradition that "the inviolability of spiritual privacy must be upheld".      In Western culture, the perception of technology tends to emphasize "instrumental neutrality"—that is, technology itself has no inherent moral character (neither good nor evil), and the key lies in the constraints of usage rules. Even though the European Union’s General Data Protection Regulation (GDPR) sets strict standards for the use of biometric data, public resistance to iris technology remains relatively low. The core reason lies in the Western cultural logic of "perceived controllability of technology": as long as a clear legal framework defines the boundaries of data use, the value of technology can be exerted while protecting privacy. This trust in "technology constrained by rules" weakens resistance to the technology itself.      In the future, the global promotion of iris technology will likely revolve around the "in-depth integration of cultural perception and technical rules". The ideal development direction is to establish a "culture-adapted technological ethics system"—one that neither ignores the unique cultural perceptions of ocular privacy in different regions nor denies the practical value of technology. Instead, cultural research should be incorporated into the early stages of technology design, aligning data protection rules with local cultural values. For example, for cultural groups that value spiritual privacy, mechanisms for transparent notification of data use and purpose-locking should be strengthened; for cultural groups that trust the instrumental nature of technology, the accountability system for data abuse should be further improved. This technology ethics framework, customized based on cultural differences, may become the key to promoting the global popularization of iris technology. IV. Artistic Integration and Value Extension      Beyond the interaction between iris technology and culture, the field of art has also launched unique explorations of iris biometrics. Such creations often take iris data as the core carrier, adhering to internationally accepted biometric technology standards while integrating diverse artistic expressions. Some transform iris features (as defined by technical standards) into concrete artistic language, while others reconstruct the connection between biometric data and identity perception through artistic techniques—achieving an integration of technological rationality and artistic sensibility.      This cross-disciplinary practice not only endows iris technology with a dimension of humanistic expression but also expands the boundaries of interaction between technology and culture from a non-practical perspective. It echoes the global trend of "culture-adapted technological development", allowing the iris— a carrier with both biological attributes and cultural significance—to demonstrate richer potential values under the dual impetus of technological application and humanistic exploration.

Breakthroughs in Iris Recognition Technology       Recently, we have achieved significant breakthroughs in the field of iris recognition technology, developing an efficient and accurate iris segmentation model. Adopting an advanced deep learning architecture, this model not only reaches industry-leading levels in accuracy but also demonstrates exceptional performance in processing speed. This technological advancement will revolutionize biometric security systems, particularly in scenarios requiring fast and accurate identity verification. Iris Recognition Technology: Principles and Development         Iris recognition, as a high-security and non-contact biometric technology, its core lies in using the unique complex textures on the human iris for identity verification. Each person's iris pattern forms after birth and remains stable throughout their lifetime, with extremely high uniqueness and non-replicability, making it an ideal choice for identity recognition.      Traditional iris recognition methods mainly include steps such as image acquisition, iris localization and segmentation, feature extraction, and feature matching. Researchers convert iris textures into digital codes through mathematical algorithms, which are then compared with templates in the database to complete identity verification. Limitations of Traditional Methods      Although traditional methods perform well in specific environments, they still face many challenges in practical applications. The quality of iris images is highly susceptible to factors such as lighting changes, blinking, eyelash occlusion, and reflections, leading to inaccurate segmentation and difficulties in feature extraction. The Necessity of Deep Learning      Faced with these limitations, traditional algorithms struggle to effectively handle complex and variable real-world data, affecting the accuracy and robustness of recognition. Therefore, introducing advanced deep learning technologies has become the key to overcoming these challenges, aiming to improve the precision and adaptability of iris segmentation and feature extraction. Innovative Model Architecture and Performance Advanced Architecture Design     Our model employs a lightweight backbone network as the encoder, integrated with an advanced attention mechanism module that simultaneously focuses on information in both channel and spatial dimensions. Multi-scale feature extraction technology allows the model to capture image information at various scales, while a UNet-like decoder structure effectively restores spatial resolution through upsampling and skip connections.Excellent Performance Metrics     After sufficient training, the model achieves outstanding results on multiple standard datasets, with a Dice coefficient exceeding 0.97 and an IoU (Intersection over Union) surpassing 0.94. This indicates the model can extremely accurately identify and segment iris regions.Ultra-High Processing Speed     In a GPU environment, the model’s inference speed reaches approximately 355 frames per second (fps); even on an ordinary CPU, it achieves a processing speed of about 40–45 fps, meeting real-time application requirements. Training and Optimization of Deep Learning Models      To ensure the iris segmentation model maintains excellent performance across different scenarios, we have adopted a systematic research, development, and optimization process. This process covers multiple links from data preparation, model training to performance evaluation, aiming to balance accuracy, robustness, and real-time processing capabilities.      At the data level, we have standardized training samples and improved the model’s stability in complex environments through diversification strategies. During the training process, we introduced advanced optimization and scheduling methods, enabling the model to continuously enhance its performance through efficient iterations.      To further ensure the precision of segmentation results, we combined multiple industry-recognized segmentation evaluation methods and paid special attention to the model’s performance in details. This has significantly improved the model’s capabilities in boundary recognition and overall adaptability.      In addition, we applied a series of regularization and performance monitoring mechanisms in research and development to prevent overfitting and ensure the model has good generalization ability. The final outcome is an efficient, compact, and easily deployable iris segmentation model that can meet high standards in practical application scenarios. Technical Verification and Application Prospects       Our model has undergone rigorous testing on multiple public datasets, including the CASIA-Iris series and MMU1 dataset. Test results show that the model not only can accurately segment iris images under standard conditions but also performs excellently when processing low-quality images—even surpassing the quality of manual annotations in some cases.      Notably, the model achieves good results on datasets with different annotation styles, which indicates it has strong generalization ability and adaptability. Security Verification Systems      High-speed and high-precision iris segmentation provides a foundation for next-generation security verification systems, which can be applied in the fields of finance, government, and enterprise security. Mobile Device Integration      The lightweight design allows the model to be easily integrated into smartphones and wearable devices, providing a convenient identity verification experience. Medical and Health Monitoring      Precise iris segmentation enables the monitoring of iris-related health conditions, opening up new applications for biometric technology in the medical field.      The successful development of this technology marks an important milestone in the field of iris recognition. We believe that with further optimization and expansion of application scenarios, this technology will play an increasingly important role in biometrics and security, providing users with safer and more convenient identity verification experiences. Future Development Directions and Research Prospects       With breakthroughs in the core model of iris recognition technology, we stand at the threshold of a new era in biometrics. Future development will focus on enhancing technical performance, expanding application boundaries, and deepening integration with other cutting-edge technologies to jointly build a safer and more convenient digital world.Technical Refinement and Miniaturization     We will continue optimizing the model to adapt to more extreme lighting conditions and complex posture changes, further lightweighting the algorithm to enable efficient operation on resource-constrained edge devices and expand deployment scope. Diversification of Application Scenarios     Beyond traditional security, iris recognition will penetrate smart homes, remote identity authentication, financial payments, and smart cars, providing seamless and high-security identity verification experiences.Cross-Technology Integration and Innovation     Iris recognition will deeply integrate with multimodal biometrics, blockchain, artificial intelligence (AI), and the Internet of Things (IoT) to form more powerful and intelligent comprehensive solutions, bringing users unprecedented security and convenience.      We are committed to advancing iris recognition technology as a core component of the future digital identity ecosystem—enhancing security protection levels, greatly simplifying user interaction processes, and driving revolutionary changes and unlimited possibilities across industries.

      When "eye-scanning unlock" on mobile phones has become a daily routine, few realize that this technology—using the eye as a "key"—has traversed a 40-year journey from laboratory research to industrialization. The story of iris recognition encapsulates humanity’s relentless pursuit of "precise identity authentication." 1. Embryonic Stage: From Discovering "Iris Uniqueness" to Theoretical Breakthroughs (1980s–1990s)    As early as the 19th century, scientists identified individual differences in iris patterns, but it was two scholars in the 1980s who transformed this observation into a theoretical framework for recognition technology: American ophthalmologist Leonard Flom and computer expert Aran Safir. On February 3, 1987, their U.S. patent became the first to systematically propose that "the iris can serve as a basis for identity recognition." It noted that the iris’s complex textures—such as folds and crypts—stabilize for life after forming during the embryonic stage, with even identical twins having distinguishable iris differences, laying the biological foundation for iris recognition.      Turning this theory into practice relied on a pivotal breakthrough by British scientist John Daugman. On March 1, 1994, his U.S. patent established an iris feature extraction algorithm based on Gabor wavelet transform. This algorithm converts iris textures into a unique 256-byte digital code, known as an "iris template." Under 1994’s technical conditions, it first controlled the false acceptance rate (FAR) below one in a million, meeting practical application standards. While Flom and Safir’s theory provided the premise for technical implementation, Daugman’s algorithm solved the core problem of "how to accurately extract features"—a technology that remains the cornerstone of iris recognition today. 2. Takeoff Stage: "Ice-Breaking" from Military to Civilian Use (2000s)      In the early 21st century, iris recognition first took root in high-security fields. In 2002, the U.S. Defense Advanced Research Projects Agency (DARPA) deployed it for military base access control. In 2005, Dubai International Airport in the UAE introduced an iris recognition system for identity verification of incoming passengers, becoming the world’s first large-scale public application case.      However, this phase had notable technical limitations: equipment was bulky (early scanners weighed several kilograms), recognition distance was only 10–20 cm, a single scan took over 3 seconds, and costs exceeded tens of thousands of dollars—making it inaccessible to everyday life. 3. Boom Stage: Smartphones Drive "Lightweighting" (2010s–Present)      On May 28, 2015, Fujitsu launched the Arrows NX F-04G, the first consumer smartphone with iris recognition, marking the technology’s entry into civilian popularization. A new turning point came in 2017 when Samsung’s Galaxy S8 integrated iris recognition with a full-screen design. Using a miniature near-infrared camera and optimized algorithms, it achieved fast recognition at 30–50 cm, even in low-light environments.      Today, iris recognition has made three major breakthroughs: recognition distance extended to 30 cm–1 meter, device size reduced to the size of a fingernail (e.g., front camera modules in phones), and algorithm processing speed increased to 1 million comparisons per second—suitable for real-time retrieval in large databases. In terms of security, iris recognition’s FAR can be as low as one in 10 million, far outperforming mainstream capacitive fingerprint recognition (FAR of ~0.001%, or one in 100,000), retaining a significant edge in identity authentication uniqueness. 4. Future: From "A Glance" to "Seamless Recognition"      Next-generation iris recognition is advancing toward "long-range, non-cooperative" capabilities. Industry research shows that long-range iris recognition has made laboratory progress, enabling identification of moving human eyes within a few meters—even with glasses. Market research predicts the global iris recognition market will grow from $3.4224 billion in 2022 to $12.6589 billion by 2030, with a compound annual growth rate (CAGR) of 18.5%. As technology matures, iris recognition is expected to integrate with AR glasses and smart car windshields, enabling seamless experiences where "identity is confirmed where the gaze reaches."      From theoretical blueprints in labs to a feature in pocket-sized phones, iris recognition’s 40 years epitomize humanity’s use of technology to decode "biological uniqueness." Chinese enterprises are accelerating efforts to reshape the global technological landscape: Wuhan Homsh Technology Co., Ltd. has independently developed an iris recognition algorithm certified by China’s Ministry of Public Security. Its embedded iris modules are used in domestic financial terminals and smart campuses, with response times controlled within 0.3 seconds. In the future, this "password" hidden in the eye will unlock even more possibilities in life, driven by continuous technological progress.