Palmprint recognition using Gabor local relative features
Xin Pan · Computer Engineering and Applications Journal · 2012
Gabor transform is an important tool for texture analysis in palmprint recognition. However, it is sensitive to the variations and uneven noises. A novel method is proposed to extract Gabor local relative features for palmprint recognition. Micro-scale invariant Gabor filters are designed to convolute with the original images; and inspired by the fractals, Gabor filtered images are divided into partitions. The relative derivations of all partitions are calculated to compare the similarity between ranges and their resided domains, which composite the feature vectors for image representation. The algorithm combines micro-scale invariant and local relativity for robust features extraction, and therefore, the recognition performance is improved. Identification experiments are executed on BJTU_PalmprintDB to test the effectiveness of the proposed method.