Face identification method and apparatus

A face recognition and to-be-recognized technology, applied in the field of pattern recognition, can solve problems such as the need to improve the accuracy of face recognition, and achieve the effect of solving universal problems, improving recognition accuracy, and enhancing robustness

Inactive Publication Date: 2015-09-16
CHONGQING UNIV OF POSTS & TELECOMM +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, the present invention provides a face recognition method and device to solve the technical problem that the accuracy of face recognition using LTP operators needs to be improved in the prior art

Method used

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  • Face identification method and apparatus
  • Face identification method and apparatus
  • Face identification method and apparatus

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Embodiment 1

[0078] see image 3 As shown, it is the first embodiment of the face recognition method provided in the embodiment of the present invention, which may include the following steps:

[0079] Step 301: Determine the LTP adaptive threshold feature value of each pixel in the face image to be recognized, and the corresponding adaptive threshold of each pixel is determined by the pixel and the gray level difference of each pixel in the neighborhood of the pixel .

[0080] Step 302: Determine the positive mode feature value and the negative mode feature value according to the LTP adaptive threshold feature value.

[0081] The face image to be recognized for face recognition adopts a grayscale image. First, the adaptive threshold of the pixel is determined according to the gray value of each pixel in the face image to be recognized and the pixels in the neighborhood of the pixel. When using the LTP operator to calculate the feature value of the pixel, the adaptive threshold of the pi...

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Abstract

The invention discloses a face identification method and apparatus, for improving the accuracy of face identification. The method comprises the following steps: determining a characteristic value of an LTP self-adaptive threshold of each pixel point in an image to be identified, wherein the self-adaptive threshold corresponding to each pixel point is determined by a gray scale difference between the pixel point and each pixel point in a neighborhood; according to the characteristic value of the LTP self-adaptive threshold, determining a positive-mode characteristic value and a negative-mode characteristic value; determining a positive-mode characteristic face and a negative-mode characteristic face, wherein the positive-mode characteristic face is composed of the positive-mode characteristic value of each pixel point, and the negative-mode characteristic face is composed of the negative-mode characteristic value of each pixel point; calculating a characteristic value histogram of each characteristic face and an information entropy weight of the characteristic face of each layer, and by use of the information entropy weights, performing weight cascading on the characteristic value histograms of the positive-mode and negative-mode characteristic faces to obtain an enhanced histogram; and calculating a chi-square distance between the enhanced histogram of the face image to be identified and the enhanced histogram of each face image with known identity, and according to the chi-square distance, determining an identification result.

Description

technical field [0001] The invention relates to the technical field of pattern recognition, in particular to a face recognition method and device. Background technique [0002] Face recognition is a biometric technology for identification based on human facial feature information. It has been applied in some fields in recent years. For example, face recognition can be applied to access control systems, attendance systems, smart phones, etc. [0003] In the face recognition technology, there are two main steps: extracting the feature vector from the face image to be recognized; comparing the feature vector with the feature vector of the image in the face database to obtain the recognition result. Among them, the first step directly affects the accuracy of face recognition results. In the prior art, there are many face recognition algorithms, such as a face recognition algorithm based on LTP (Local Binary Patterns, local ternary pattern) operator for feature extraction, LTP o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
Inventor 李伟生王立逗
Owner CHONGQING UNIV OF POSTS & TELECOMM
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