Sparse Representation Face Recognition Method Combining Shape Features

A shape feature and face recognition technology, applied in the field of face recognition, can solve the problems of high image registration requirements and achieve high face recognition rate

Inactive Publication Date: 2011-12-28
JIANGSU TSINGDA VISION TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0021] This method is robust to changes in facial illumination and expression, but has high requirements for image registration

Method used

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  • Sparse Representation Face Recognition Method Combining Shape Features
  • Sparse Representation Face Recognition Method Combining Shape Features
  • Sparse Representation Face Recognition Method Combining Shape Features

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Embodiment Construction

[0058] The sparse representation face recognition method combined with shape features proposed by the present invention is described in detail in conjunction with the accompanying drawings and embodiments as follows, including the following steps:

[0059] 1) Extract the texture features of all the face images in the training set, obtain the texture feature vectors of all the face images in the training set, arrange the texture feature vectors of all the face images in the training set to form a texture feature matrix A1, and extract the texture feature vectors in the texture feature matrix One or more lines of one or more lines are used as a category of the training set, and one category corresponds to multiple face images of a person in the training set;

[0060] 2) Extract the shape features of all the face images in the training set, obtain the shape feature vectors of all the face images in the training set, arrange the shape feature vectors of all the face images in the t...

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Abstract

The invention relates to a face recognition method with sparse representation combined with shape features, which belongs to the field of image processing. The method includes: extracting texture features and shape features from all face images in a training set based on constrained sampling to obtain texture feature matrices and shape features Matrix, one category of the texture feature matrix and shape feature corresponds to multiple face images of a person in the training set; the face image of the person to be recognized is extracted based on constrained sampling for texture feature extraction and shape feature extraction, and the image to be recognized is obtained The texture feature vector; for each category in the training set, calculate the texture residual and shape residual corresponding to the training category; the shape feature vector of the image to be recognized is represented by the linear coefficient of the shape feature vector of the training set; the obtained The face to be recognized corresponds to the category of the training set corresponding to the maximum value of the comprehensive similarity of the class as the recognition result of the person to be recognized; this method has a higher face recognition rate.

Description

technical field [0001] The invention belongs to the technical fields of image processing, computer vision and pattern recognition, and in particular relates to a face recognition method. Background technique [0002] Biometric feature recognition technology is an effective technology for identification, and the fastest growing recently is face recognition technology and biometric feature recognition technology integrated with face recognition technology. [0003] Currently existing face recognition methods mainly recognize the entire face, and among many recognition methods, principal component analysis (PCA-Principal Component Analysis), elastic matching, neural network, geometric features and other methods are mainly used. [0004] At the same time, the difficulty of face recognition lies in: [0005] (1) Face plastic deformation caused by expression [0006] (2) Face diversity caused by posture [0007] (3) Face changes caused by age [0008] (4) The multiplicity of f...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
Inventor 苏光大王晶陈健生刘炯鑫任小龙
Owner JIANGSU TSINGDA VISION TECH
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