Hand vein recognition based on PCET

A new feature extraction algorithm based on polar harmonic transforms (PHT) is presented, the accomplishment of the new algorithm involves several steps. First, we design the power-controlled multispectral vein acquisition handset to establish high-quality hand vein database. Second, we propose an improved valley-shaped enhancement operator with Niblack algorithm to realize vein segmentation. Third, we design experiments to compare the capability of the several invariant moments including Hu, Zernike, PST, PCT, PCET on the feature description of the different samples and the same samples with different geometric changes. Finally we choose PCET to do the matching experiment and we also use Hu to do the experiment so as to show the superiority of the PCET. The result is that the PCET can achieve an error equation rate of 0.861% and the Hu just achieves 14.51%.