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Method for extracting human face illumination invariant features by utilizing Wallis operator

A technology with constant illumination and feature extraction, applied in the field of pattern recognition, it can solve the problem of face recognition not being completely solved, and achieve the effect of fast recognition speed, simple method and high recognition rate.

Inactive Publication Date: 2017-12-08
CHONGQING THREE GORGES UNIV
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Problems solved by technology

However, face recognition is still a difficult problem that has not been completely solved, and the problem of illumination change is one of the key problems that have not been solved.

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  • Method for extracting human face illumination invariant features by utilizing Wallis operator
  • Method for extracting human face illumination invariant features by utilizing Wallis operator
  • Method for extracting human face illumination invariant features by utilizing Wallis operator

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Embodiment Construction

[0025] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0026] Such as figure 1 Shown, a kind of face illumination invariant feature extraction method utilizing Wallis operator, comprises the following steps:

[0027] (1) Transform the original image into the logarithmic domain;

[0028] (2) In the logarithmic domain, use the Wallis operator to sharpen the face, extract the detailed features of the face, and eliminate the illuminated part of the face at the same time to obtain the invariant features of the face's illumination.

[0029] According to the light reflection model, any grayscale face image I(x,y) can be regarded as the product of the reflection component R(x,y) and the light component L(x,y), that is, I(x,y)=R (x, y) L (x, y); In the step (1), the face image is logarithmically transformed, so that the reflection component and the light component are converted from multiplication to add...

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Abstract

The invention discloses a method for extracting human face illumination invariant features by utilizing a Wallis operator. The method comprises the following steps of: transforming an original image to a logarithm domain; and sharpening a human face image by utilizing the Wallis operator, extracting human face detail features, and eliminating human face illumination components at the same time, wherein the obtained result is a to-be-extracted human face illumination invariant feature. The method has a certain inhibiting effect for illuminations at different angles; the identification rate of the processed human face images is higher than the human face identification rate obtained through existing method; and according to the method, light processing is carried out on human face images by adoption of logarithm transformation and the Wallis operation, so that the method is simple and high in identification speed.

Description

technical field [0001] The invention relates to the technical field of pattern recognition, in particular to a method for extracting features invariant to illumination of a human face utilizing a Wallis operator. Background technique [0002] As one of the biological characteristics, the human face, as the most common physiological structure innate to the human body, has direct friendliness that other biological characteristics do not have, and is an important object in the field of biometric recognition research. Face information has the advantages of being non-replicable, non-stealable, simple and intuitive, and is an important strategic resource that commercial banks should reserve and discover value in the era of big data. With technological changes and popularization of applications, the cost of building a large-scale, distributed face database and recognition system has been continuously reduced, and the accuracy of recognition has been continuously improved. Therefor...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06K9/36G06K9/00
CPCG06V40/171G06V10/20G06V10/60G06V10/462
Inventor 聂祥飞王元元何雪熊文怡杨志军
Owner CHONGQING THREE GORGES UNIV
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