A Watershed Algorithmic Approach for Gray-Scale Skeletonization in Thermal Vein Pattern Biometrics

In vein pattern biometrics, analysis of the shape of the vein pattern is the most critical task for person identification. One of best representations of the shape of vein patterns is the skeleton of the pattern. Many traditional skeletonization algorithms are based on binary images. In this paper, we propose a novel technique that utilizes the watershed algorithm to extract the skeletons of vein patterns directly from gray-scale images. This approach eliminates the segmentation stage, and hence prevents any error occurring during this process from propagating to the skeletonization stage. Experiments are carried out on a thermal vein pattern images database. Results show that watershed algorithm is capable of extracting the skeletons of the veins effectively, and also avoids any artifacts introduced by the binarization stage.