Human-face identification method based on local contrast pattern

Abstract

The invention relates to a human-face identification method based on a local contrast pattern (LCP) and belongs to the technical field of pattern identification. The human-face identification method based on the LCP includes that human-face database images are preprocessed firstly so as to weaken influences of illumination on feature extraction; calculation of LCP feature matrixes is performed on training set images and testing set images respectively; the obtained LCP feature matrixes are converted into a column diagram; calculation of feature similarity of testing samples and training samples is performed on the column diagram by adopting a chi-square (X<2>) distance function; and the testing samples are classified and identified by using a nearest neighbor classifier. The human-face identification method based on the LCP has high human-face identification accuracy.

Description

technical field [0001] The invention relates to the technical field of pattern recognition, in particular to a face recognition method based on a partial contrast pattern. Background technique [0002] In recent years, face recognition technology has made great progress, and various face recognition algorithms have been proposed and improved continuously, and many face recognition systems have been put into practical use at present. However, there are still many problems in face recognition research that have not been well resolved. The reason is that the face image will be affected by factors such as illumination changes, expression changes, and occlusions during the acquisition process. The interference is the most serious. In an environment where the lighting cannot be controlled, such as outdoors, the face features are obviously affected by the direction and intensity of the light and produce nonlinear changes, which makes face recognition difficult. The difference bet...

AI Technical Summary

Problems solved by technology

[0005] Since the local binary pattern (LBP) method only considers the size relationship between the central pixel and the gray value of neighboring pixels, the gray value of the pixel in the local area of ​​the image will be completely different, but the local binary pattern (LBP) obtained by them will be completely different. ) eigenvalues ​​are exactly the same, which affects the recognition rate of the face recognition method based on the local binary pattern (LBP), because the local binary pattern (LBP) method does not consider the difference between the central pixel and the neighboring pixels. The contrast information of the gray value, and the difference of the contrast information is just a very important feature to distinguish the texture of the local area

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