Method for performing face recognition by combining rarefaction of shape characteristic

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: 2010-09-01
JIANGSU TSINGDA VISION TECH
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Problems solved by technology

[0021] This method is robust to changes in facial illumination

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  • Method for performing face recognition by combining rarefaction of shape characteristic
  • Method for performing face recognition by combining rarefaction of shape characteristic
  • Method for performing face recognition by combining rarefaction of shape characteristic

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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 method for performing face recognition by combining the rarefaction of shape characteristic, belonging to the image processing field. The method comprises the following steps: performing textural characteristic extraction and shape characteristic extraction to all the facial images in a training set based on constrained sampling, obtaining textural characteristic matrix and shape characteristic matrix, corresponding one type of the textural characteristic matrix and shape characteristic matrix to a plurality of face images of one person in the training set respectively; performing textural characteristic extraction and shape characteristic extraction to the face image of a person to be identified based on constrained sampling, obtaining the textural characteristic vector of a image to be identified; calculating the textural residual error and shape residual error of each type in the training set; using the linear coefficient of the shape characteristic vector of the training set to represent the shape characteristic vector of the image to be identified; and using the type of the training set with the maximum comprehensive similarity to the face to be identified as the identifying result of the person to be identified. The method of the invention has higher face recognition.

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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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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