A kind of iris verification method and system based on iris circumscribed rectangle graph

Abstract

The invention discloses an iris verification method and system based on an iris circumscribed rectangular graph, belonging to the field of iris verification. Including: training stage: training iris feature extraction network using training sample sets composed of iris circumscribed histograms of different individuals; iris verification stage: collecting identity and iris images of users to be verified, positioning their iris images, and obtaining iris circumscribed histograms , input to the trained iris feature extraction network to obtain the iris embedding vector to be verified; determine the input iris embedding vector according to the identity of the user to be verified; compare the iris embedding vector to be verified and the input iris embedding vector to determine whether they belong to the same individual. The invention converts the robustness problem of iris segmentation into the problem of neural network feature extraction, and the robustness problem of neural network feature extraction is solved by neural network training, so the circumscribed rectangle positioning of the outer circle of the iris is used to reduce the complexity of iris preprocessing to improve the accuracy of iris verification.

Description

technical field [0001] The invention belongs to the field of iris verification, and more specifically relates to an iris verification method and system based on an iris circumscribed histogram. Background technique [0002] With the continuous development of global informatization and digital technology, technology brings convenience to society, but also brings information security issues. In order to protect the safety and reliability of information, more reliable authentication methods are needed. Traditional authentication methods use special items (such as personal documents) or special passwords (such as user IDs and passwords) to verify the legitimacy of users. These methods are simple and easy. realized, and thus widely used. However, these methods have many limitations. Special items are easy to be lost and forged, and special passwords are easy to be stolen. Therefore, traditional identification technology can no longer meet the needs of life. In order to solve th...

AI Technical Summary

Problems solved by technology

[0004] However, unlike other computer vision tasks based on deep learning, especially face recognition, there are not many works that make full use of deep learning to measure iris features. In recent years, some people have proposed to use deep neural networks for iris recognition, such as DeepIrisNet model, but these models require fine segmentation of the original iris area, and most of them use classification models instead of depth measurement models, which require a large number of data sets for support and are easy to overfit, difficult to train, and Not robust enough for complex common scenarios

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