Palmprint verification with XOR-SUM Code
The proposed work aims to improve the performance of palmprint recognition system by reducing the size of templates. Discrete Wavelet Transform assists in scaling down the size of extracted Region of Interest of palmprint approximately by a factor of 16, while preserving the potential information used to discriminate among different palms. This work proposes XOR-SUM Code, which is based on the fusion of the real and the imaginary Palm Code images for different orientations (say, \(N\)). The fused images of all orientations are added together to get line features of palmprint. The resulting image is then coded into \(\left\lceil (N+1)/2 \right\rceil \) bits to get line features of reduced size. Experiments are carried out on Hong Kong PolyU palmprint database that contains 8000 palmprint images of 400 different palms. XOR-SUM Code technique is compared with Palm Code, Competitive Code, and Contourlet Transform-based techniques in terms of Equal Error Rate (EER), Decidability Index (DI), and Genuine Acceptance Rate (GAR). The XOR-SUM Code technique results in EER, DI, and GAR of 1.83%, 4.4433, and 98.17% respectively.
xor-sum code equal error rate (eer) decidability index (di) genuine acceptance rate (gar) roi discrete wavelet transform (dwt) gabor filter