Reconstruction in Gabor Response Domain for Efficient Finger-knuckle-Print Verification

The finger knuckle print (FKP) based personal identification has achieved much interest. One of the disadvantages of the generally used Gabor filter based Competitive Coding method is that it is sensitive to variations caused in image acquisition stage. To handle this problem, researchers have proposed a reconstruction based scheme in original image pixel domain. However, the reconstruction in original image domain may lose much valuable directional information extracted by Gabor filters with different orientations. Compared with the previous methods, in this paper, we propose to perform reconstruction in Gabor filter response domain. For each orientation, we reconstruct the Gabor response of a query image using the responses in the template database. Thus, the directional information contained in the image is fully utilized. Then, we binarize each reconstructed responses for feature coding and matching with the constructed "mask", which considers not only the reconstructive error but also the Gabor response in a specific location. The mask can characterize the significance of a specific location along a specific orientation. Finally, by using a score level adaptive binary fusion rule, the matching distances before and after reconstruction are adaptively fused. The experimental results conducted on the benchmark PolyU FKP database show the performance advantage of the presented method.