Finger-shape extraction and expansion by wavelet transform and hand-shape analysis and recognition

Abstract

This research uses the object extracting technique to extract the -thumb, index, middle, ring, and small fingers from the hand images. The algorithm developed in this research can find the precise locations of the fingertips and the finger-to-finger- valleys. The extracted fingers contain many useful geometry features. One can use these features to do the person identification. The geometry descriptor is used to transfer geometry features of these finger images to another feature-domain for image-comparison. Image is scaled and the reverse Wavelet Transform is performed to the finger image to make the finger image has more salient feature. Image subtraction is used to exam the difference of the two images. This research uses the finger-image and the palm image as the features to recognize different people. In this research, totally eighteen hundred and ninety comparisons are conducted. Within these eighteen hundred and ninety comparisons, two hundred and seventy comparisons are conducted for self-comparison. The other sixteen hundred and twenty comparisons are conducted for comparisons between two different persons' finger images. The false accept rate is 0%, the false reject rate is 1.9%, and the total error rate is 1.9%.