An Identity Recognition System Based on Face Image

Abstract

The invention provides an identity recognition system based on a face image, comprising a face image acquisition subsystem, a face image processing recognition subsystem, and a display subsystem connected in sequence; the image acquisition subsystem is used to collect and store the face image to be identified, The face image processing and recognition subsystem is used to recognize the collected and stored face images to be recognized, obtain the identity recognition result, and display the identity recognition result through the display subsystem. The beneficial effects of the present invention are: when the face image needs to be recognized, the face image to be recognized is collected and stored by the face image collection subsystem, and then the collected and stored face image to be recognized is processed and stored by the face image processing and recognition subsystem The face image is recognized to obtain the identification result, and the display subsystem displays the identification result, which can realize the effective authentication of the identity, so as to realize real-name authentication, network account security, account login convenience, and improve the security of identity authentication .

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an identity recognition system based on a face image. Background technique [0002] The existing automatic face recognition system can achieve satisfactory results when the user cooperates and the acquisition conditions are ideal. However, when the user does not cooperate and the acquisition conditions are not ideal, such as poor lighting, occlusion, posture changes, etc., the recognition effect of the existing system will plummet. The feature extraction method based on local structure based image decomposition (IDLS) first measures the structural relationship between the central macropixel and its neighboring macropixels in the local window through ridge regression to describe the local structure information of the image, and then according to the local structure information, The image is decomposed into multiple sub-images, and finally the multiple sub-images are unif...

AI Technical Summary

Problems solved by technology

However, this method does not perform specific processing on the image before feature extraction. With the large increase in the size of face data, the face recognition rate will decrease, resulting in unsatisfactory subsequent image processing efficiency, which in turn causes reduction in reliability

[0003] In summary, there are problems of low efficiency and reliability in image recognition in the prior art

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