Sparse representation face recognition method based on intra-class variation dictionary and training image

Abstract

The invention discloses a sparse representation face recognition method based on an intra-class variation dictionary and a training image, for solving the problems of limitation of the existing method in the aspects of small sample, uneven illumination, face shielded and expression variation and increasing the face recognition accuracy. The method comprises the following implementation steps of: (1) extracting image characteristics from a training image set and a test face image so as to form a training image matrix and a test image vector, and respectively normalizing the training image matrix and the test image vector; (2) collecting image texture differences of the same face in different external environments from a face database so as to form the intra-class variation dictionary of the face; (3) representing the test image as a linear combination of the training image matrix and the intra-class variation dictionary, and acquiring the optimal sparse representation coefficient through the L1 norm minimization criterion; and (4) acquiring a residual between the original test image and a recombination image recombined from each type of the training image and the intra-class variation dictionary, and substituting the residual into a type judgment formula so as to acquire a recognition result.

Description

technical field [0001] The invention relates to a face recognition method, more precisely, to a sparse representation face recognition method based on intra-class variation dictionaries and training images, and belongs to the technical field of computer image processing and pattern recognition. Background technique [0002] Face recognition is a technology that uses computers to analyze face images, extract effective identification features from them, and realize identity authentication. Compared with biometric features such as fingerprints, iris, and palm prints, the advantages of using face for identity authentication are easy to use, low cost, and concealed operation. Its application scenarios are very extensive, such as public security monitoring, judicial certification, civil aviation security inspection, port access control, intelligent access control, etc. [0003] A face recognition system usually includes three parts: face detection, feature extraction and recognit...

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Problems solved by technology

[0009] In view of this, the purpose of the present invention is to provide a kind of face recognition method based on the sparse representation of intra-class variation dictionary and training images, utilize the intra-class variation dictionary and the sparse representation of training images to solve the problems in the prior art that face images are in the small Insufficient description of differences in samples, uneven illumination, face occlusion and expression changes, and while reducing the number of face training images, improve the face recognition accuracy in complex environments such as illumination, occlusion or expression

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