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Human face identification method based on fisher low-rank matrix restoration

A low-rank matrix and face recognition technology, applied in the field of pattern recognition, can solve the problems of poor recognition performance, achieve the effect of removing sparse noise and good face recognition performance

Inactive Publication Date: 2014-03-12
ZHEJIANG NORMAL UNIVERSITY
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Problems solved by technology

[0009] The technical problem to be solved by the present invention is that when the training image and the test image are all damaged, the recognition performance of the common face recognition method is poor, and a kind of face recovery based on Fisher low-rank matrix with good recognition accuracy is provided. recognition methods

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  • Human face identification method based on fisher low-rank matrix restoration
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Embodiment Construction

[0047] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0048] Such as Image 6 Shown embodiment is a kind of face recognition method based on Fisher's low-rank matrix restoration, comprises the steps:

[0049] Step 100, the computer reads the training data matrix X=[X 1 , X 2 ,...,X c ], the training data matrix is ​​composed of face image matrices of c individuals; where, X c An image data matrix composed of several images of the person numbered c; the face image y to be tested is test stored in a computer;

[0050] Step 200, the computer calculates the low-rank matrix A of the training data matrix X, including the following steps:

[0051] Step 201, set p=1, k=0, μ k , ρ, η, λ and convergence error e; where μ k >0, ρ>1, 0 in, is a random initial value of A, is a random initial value of E, is the random initial value of the Lagrange multiplier matrix;

[0052] calculate Among them...

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Abstract

The invention discloses a human face identification method based on fisher low-rank matrix restoration. According to the method, the human face identification problem is subjected to modeling under a low-rank matrix restoration framework, and in addition, a fisher discriminating criterion is combined for carrying out regularized discriminating restriction. In the human face identification problem, label information of all training images are known, the class-by-class discriminating criterion is utilized for regularizing the representation base obtained through the low-rank matrix restoration through being enlightened by the fisher criterion, and the discriminating performance of the algorithm in the human face identification is improved. The human face identification method has the characteristics that most sparse noise can be effectively removed; when both training images and test images are damaged, the human face identification performance is obviously superior to other algorithms.

Description

technical field [0001] The invention relates to the technical field of pattern recognition, in particular to a face recognition method based on Fisher low-rank matrix restoration with good recognition accuracy. Background technique [0002] The identity authentication technology based on biometric features has an increasingly important position and role in social life. Among many biometric authentication methods, the recognition and authentication based on human facial features has been widely concerned and valued because of its advantages of non-invasiveness, low cost, good concealment, and no special cooperation from the subject, and has a wide range of applications. prospect. [0003] In terms of functions, face recognition can be divided into two categories: face recognition and face authentication. Face recognition refers to comparing one or more face images to be identified with the face images of all people stored in the database to determine the most similar person...

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Application Information

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IPC IPC(8): G06K9/00G06K9/66
Inventor 郑忠龙张海新贾泂
Owner ZHEJIANG NORMAL UNIVERSITY
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