Two novel color local descriptors for face recognition

Abstract This research paper introduces two novel color descriptors for Face Recognition (FR) called as Color ZigZag Binary Pattern (CZZBP) and Color Median Block ZigZag Binary Pattern (CMBZZBP). The pixels aligned in ZigZag manner are utilized for producing the feature size of both the proposed descriptors. For first proposed descriptor, the ZigZag features are extracted from 3 color components of the RGB color space format, which are concatenated to produce the entire feature size of the CZZBP descriptor. Specifically, on 3 color components i.e. R, G and B, the features are extracted by utilizing three different type of ZigZag binary patterns called as ZZBP1, ZZBP2 and ZZBP3. The ZZBP1 is applied on the R component, ZZBP2 is applied on the G component and ZZBP3 is applied on the B component. In the second proposed descriptor, the same concept is employed on medians computed from 9 different blocks of 9 × 9 pixel window, where each block size is 3 × 3. To produce compact feature size, PCA is employed and classification is performed by SVMs and NN. The 2 databases used for performance evaluation are GT and Faces94. Experiments reveals effectiveness of the proposed descriptors than compared descriptors. Among all descriptors, CMBZZBP is most impressive.

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