Identity recognition system based on human face image

Abstract

The invention provides an identity recognition system based on a human face image, and the system comprises a human face image collection subsystem, a human face image processing and recognition subsystem and a display subsystem, wherein the human face image collection subsystem, the human face image processing and recognition subsystem and the display subsystem are connected sequentially. The human face image collection subsystem is used for collecting and storing a to-be-recognized human face image, and the human face image processing and recognition subsystem is used for recognizing the collected and stored to-be-recognized human face image, and obtaining an identity recognition result. The display subsystem displays the identity recognition result. The beneficial effects of the invention are that the human face image collection subsystem is used for collecting and storing the to-be-recognized human face image during the recognition of a human face image, and then the human face image processing and recognition subsystem is used for recognizing the collected and stored to-be-recognized human face image and obtaining the identity recognition result; the display subsystem displays the identity recognition result; the system can achieve the effective authentication of the identity, can achieve the real-name authentication, network account safety and account logging-in convenience and improves the identity authentication safety.

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 under the conditions of user cooperation and ideal collection conditions. However, when the user does not cooperate and the acquisition conditions are unsatisfactory, such as poor light, obstruction, and posture changes, the recognition effect of the existing system will decline linearly. The feature extraction method based on local structure based image decomposition (IDLS) first uses ridge regression to measure the structural relationship between the central macro pixel in the local window and its neighbor macro pixels 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-imag...

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

Images