Face image convex-and-concave pattern texture feature extraction and recognition method

Abstract

The invention relates to a face image convex-and-concave pattern texture feature extraction and recognition method, and belongs to the technical field of pattern recognition. The method includes the steps: dividing an image into pieces; performing bilinear interpolation on each piece of the image; calculating the local difference of each pixel point in each piece of the image in eight directions, and performing convex-and-concave pattern coding on the local difference so that a multi-resolution local convex-and-concave pattern matrix of each piece of the image is obtained; extracting the histogram characteristic vector of the multi-resolution local convex-and-concave pattern matrix of each piece of the image, and connecting the histogram characteristic vectors of all the pieces of the image in sequence to obtain the histogram characteristic vector of the original image; and finally, sending the histogram characteristic vector of the image to the nearest classifier based on chi-square statistics for classification and recognition. Local differential convex-and-concave pattern coding is performed on the local difference of the image, and the local convex-and-concave pattern represents a feature of fluctuating changes in the local gray scale of the image. The method exhibits a great image local texture description capability, and can effectively recognize human faces in an illumination environment.

Description

technical field [0001] The invention relates to a method for extracting and identifying texture features of a convex-convex pattern of a human face image, and belongs to the technical field of pattern recognition. Background technique [0002] Local binary pattern (LBP) [L.Wang and D.C.He, "Texture classification using texture spectrum", Pattern Recognition, vol.23, pp.905-910, 1990.] is an important image feature The extraction operator has the characteristics of small amount of calculation and effective. Although LBP has achieved great success in the fields of computer vision and pattern recognition, its working mechanism still needs to be improved. Dominant local binary patterns (DLBP) [S.Liao, M.W.K.Law, and A.C.S.Chung, "Dominant local binary patterns for texture classification," IEEE Trans.Image Process., vol.18, no.5 , pp.1107–1118, May 2009.] On the basis of all the LBP modes of the statistical image, the higher frequency modes are screened out, and the high freque...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a method for extracting and identifying texture features of convex-convex patterns of human face images, which is used to solve the problem of human face recognition under illumination environment

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