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Image sparse representation-based robust human face identification method

A sparse representation, robust human technology, applied in the field of robust face recognition, can solve the problem of low recognition rate of face recognition system

Active Publication Date: 2018-10-16
WUHAN UNIV OF SCI & TECH
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Problems solved by technology

This method can solve the technical problem of low recognition rate of the face recognition system caused by variable factors such as illumination, posture, expression, etc. The feature extracted by this method has strong representation ability and better face classification effect

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  • Image sparse representation-based robust human face identification method
  • Image sparse representation-based robust human face identification method
  • Image sparse representation-based robust human face identification method

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Embodiment Construction

[0039] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0040] figure 1 The flow chart of the robust face recognition method based on image sparse representation proposed by the present invention, combined with figure 1 The implementation process of the present invention is described in detail:

[0041] Step S1, face image preprocessing;

[0042] Grayscale and scale normalization preprocessing is performed on the face images in the face database, and all images are normalized to a size of 32×32 pixels.

[0043] Step S2, feature extraction of multi-directional Gabor feature maps;

[0044] The present invention adopts the feature extraction method of multi-directional Gabor feature map (Multi-directional Gabor Feature Maps, MGFM), such as figure 2 As shown in Fig. 1, the face image is first subjected to multi-directional and multi-scale Gabor transformation, and then the Gabor f...

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Abstract

The invention provides an image sparse representation-based robust human face identification method. The method comprises the steps of firstly performing multi-direction and multi-scale Gabor transformation on a human face image; secondly fusing Gabor features of different scales in the same direction to obtain multi-direction feature graphs; thirdly extracting Gist features from the multi-direction feature graphs and endowing the Gist features with different weights; fourthly cascading the weighted Gist features of the multi-direction feature graphs to form a human face image eigenvector; andfinally performing classification by utilizing sparse representation to realize human face identification. The method can solve the technical problem of relatively low identification rate of a humanface identification system caused by variable factors such as illumination, poses, expressions and the like; the features extracted by the method are good in representation capability; and a better human face classification effect is achieved.

Description

technical field [0001] The invention belongs to the field of image processing and biological feature recognition, and in particular relates to a robust face recognition method based on image sparse representation. Background technique [0002] In the research fields of computer vision, biometric recognition, and artificial intelligence, face recognition has always been an important topic studied by many scholars. Through the development of recent decades, face recognition technology has achieved great results. Although some representative face recognition algorithms have emerged, these face recognition algorithms are restricted by many conditions in practical applications. For example, lighting, posture, and expression, these constraints are not only difficult points in face recognition technology, but also hot spots for researchers to study. [0003] In order to solve the problems existing in face recognition technology, Wright et al. proposed a face recognition method bas...

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V40/161G06V40/168G06V40/172
Inventor 张培徐望明刘召徐天赐
Owner WUHAN UNIV OF SCI & TECH
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