Co-occurrence matrix and its statistical features as a new approach for face recognition

Authors : Alaa ELEYAN, Hasan DEMİREL

Pages : 97-107

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Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :In this paper, a new face recognition technique is introduced based on the gray-level co-occurrence matrix insert ignore into journalissuearticles values(GLCM);. GLCM represents the distributions of the intensities and the information about relative positions of neighboring pixels of an image. We proposed two methods to extract feature vectors using GLCM for face classification. The first method extracts the well-known Haralick features from the GLCM, and the second method directly uses GLCM by converting the matrix into a vector that can be used in the classification process. The results demonstrate that the second method, which uses GLCM directly, is superior to the first method that uses the feature vector containing the statistical Haralick features in both nearest neighbor and neural networks classifiers. The proposed GLCM based face recognition system not only outperforms well-known techniques such as principal component analysis and linear discriminant analysis, but also has comparable performance with local binary patterns and Gabor wavelets.
Keywords : Key words Face recognition, gray level co occurrence matrix, Haralick features