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This paper proposes a novel offline text-independent writer identification method based on scale invariant feature transform (SIFT), composed of training, enrollment, and identification stages. In all stages, an isotropic LoG filter is first used to segment the handwriting image into word regions (WRs). Then, the SIFT descriptors (SDs) of WRs and the corresponding scales and orientations (SOs) are...
Palm vein recognition systems are one of the newest biometric technologies to have arisen in the recent past. Palm vein authentication uses the vascular patterns of an individual's palm of the hand as personal identification data. Veins and other subcutaneous features in the human hand present large, robust, stable and largely hidden patterns. In the proposed work, we present a palm vein verification...
This paper proposes a novel approach for offline text-independent writer identification. The proposed approach extracts two new features: Stroke Fragment Histogram (SFH) and Local Contour Pattern Histogram (LCPH). For SFH extraction, a handwriting image is firstly segmented into many stroke fragments (SFs) by using the proposed fragment segmentation method based on sliding window. Then all SFs extracted...
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