Homsh Technology has recently officially launched its independently developed OVAI (Optical Valley Artificial Intelligence) Iris Recognition System. Adopting deep learning technology, this system has achieved significant technological breakthroughs in recognition accuracy and anti-interference capability under non-ideal image conditions, which is expected to promote the popularization of iris recognition technology in more extensive scenarios.
As an important branch of biometric technology, iris recognition has broad application prospects in finance, security, mobile devices and other fields. However, traditional iris recognition algorithms encounter numerous technical challenges in practical applications.
According to industry research data, the recognition success rate of traditional iris recognition systems decreases significantly in complex environments. Practical scenario issues such as insufficient light, glasses reflection, eyelash occlusion, long-distance recognition, and resolution limitations of smart device cameras have become major bottlenecks restricting the popularization of the technology.
In addition, traditional algorithms have a contradiction between processing efficiency and recognition accuracy: high-precision algorithms often require long processing time, while fast algorithms struggle to ensure accuracy, making it difficult to balance user experience and security.
The OVAI system reconstructs the iris recognition algorithm architecture using deep learning technology. Its core innovation lies in the adoption of an end-to-end optimization design, integrating the traditionally separated steps of preprocessing, segmentation, and recognition into a unified neural network model.
Multi-Level Intelligent Segmentation Technology
The OVAI system has developed three-level progressive segmentation technology. The coarse segmentation stage quickly locates the eye region, the fine segmentation stage accurately extracts iris boundaries, and the detailed segmentation stage precisely eliminates the pupil and interference factors. Compared with traditional edge detection methods, this technology significantly improves segmentation accuracy in complex scenarios.
CBAM Dual Attention Mechanism
The system integrates the Convolutional Block Attention Module (CBAM), optimizing the feature extraction process through two dimensions: channel attention and spatial attention. Channel attention automatically identifies important feature information, while spatial attention accurately locates key regions, enabling more precise iris positioning and feature extraction.
End-to-End Joint Optimization
Different from the traditional method of optimizing each module independently, OVAI adopts integrated training for the entire process of preprocessing-segmentation-recognition and supports multi-task learning. It can output segmentation results and image quality evaluation simultaneously, effectively eliminating the problem of error accumulation.
According to test data released by Homsh Technology, the OVAI system has made breakthroughs in several key technical indicators:
• Superb robustness: Accurate recognition even under harsh conditions such as blurriness, occlusion, and low light
• Long-distance recognition capability: Solved the technical problem of blurry image segmentation in long-distance scenarios that troubled traditional algorithms
• Anti-interference capability: Effectively handles common interference factors like glasses reflection and eyelash occlusion
• End-to-end optimization: Avoids error accumulation of traditional solutions through joint training of preprocessing-segmentation-recognition
• Intelligent quality assessment: AI automatically judges the quality of input images and can reject low-quality inputs
• Quantifiable model: Supports INT8 quantization deployment to adapt to different hardware environments
• GPU acceleration support: Improves processing efficiency through hardware acceleration optimization
The technical breakthroughs of the OVAI system are expected to drive the popularization of iris recognition in multiple fields. In the consumer electronics sector, this technology can enable ordinary smart devices to possess professional iris recognition capabilities. In the financial security field, it can provide higher-security identity authentication for scenarios such as mobile payments and ATM withdrawals. In the enterprise security field, it can support applications like access control systems and data center access management.
Industry experts believe that the OVAI system has addressed key pain points of traditional iris recognition in practical applications, especially its recognition capability under non-ideal image conditions, thus removing important technical obstacles for the commercial promotion of iris recognition technology.
The OVAI system provides standardized SDK interfaces and supports multi-platform integration and deployment. Designed with edge computing needs in mind, it can perform local processing on mobile devices without relying on cloud services, ensuring both response speed and data privacy protection requirements.
The system also supports various hardware environments, from professional biometric devices to ordinary smart device cameras, reducing the hardware threshold for technical application.
Industry observers believe that the release of the OVAI system marks the official entry of iris recognition technology into the AI-driven era. The introduction of deep learning technology has not only solved the technical limitations of traditional algorithms but also provided a new development path for future technological evolution.
With the continuous development of artificial intelligence and the improvement of computing hardware performance, biometric technology based on deep learning is expected to replace traditional authentication methods in more scenarios, driving technological upgrading across the entire identity authentication industry.
Dr. Yi Kaijun, Chairman of Wuhan Homsh Technology Co., Ltd., stated when talking about the release of the OVAI system: "This technological breakthrough signifies that iris recognition is entering the intelligent 4.0 era. The limitations of traditional iris recognition algorithms in the face of complex real-world scenarios have long been a key bottleneck restricting industry development. Through the innovative application of deep learning technology, the OVAI system has not only solved core technical problems such as long-distance recognition, complex lighting, and occlusion interference but, more importantly, provided a brand-new technical development path for the entire biometrics industry."
Dr. Yi Kaijun further pointed out: "The in-depth integration of artificial intelligence and biometric technology is an inevitable trend. We firmly believe that with the continuous maturity of AI technology and the steady improvement of hardware performance, deep learning-based biometrics will become the mainstream technology for future identity authentication. Homsh Technology will continue to increase R&D investment, maintain its leading technical advantages, and actively promote the industrial application of OVAI technology to contribute to building a more secure and trustworthy digital world."
"The successful development of OVAI demonstrates our team's persistent pursuit and profound accumulation in technological innovation. We hope this technology can truly solve the pain points users encounter in practical applications, allowing iris recognition to move from laboratories to thousands of households, and enabling more people to enjoy the convenience and security brought by technological progress," Dr. Yi Kaijun concluded.
Homsh Technology is a technology enterprise focusing on iris recognition technology R&D, committed to promoting the development and application of biometric technology through technological innovation. The company has a complete R&D system for iris recognition technology, with rich experience in algorithm optimization, chip design, system integration, and productization.
The OVAI project is an important achievement of Homsh Technology in the integration of artificial intelligence and biometric technology, representing new progress in the company's technological innovation and industrial application.
