Direct gray-scale extraction of topographic features for vein recognition

Binarization processing is a key step in most vein pattern recognition, but may create flaws such as leakage of some feature information. In order to overcome this problem, a new approach is explored in this paper which can extract topographic features directly from gray-scale vein images without binarization processing. First, an extreme graph of directional fields (EGDF) is calculated according to neighborhood information of every pixel, and then the intravenous main ridge of the image can be separated step by step from EGDF with the defined constraint template sets. After that, the sub-ridge is extracted from end points of the main ridge in range constraint image with the tracing method of maximal neighboring point. According to contrast experiment the proposed method is better than the traditional processing (performing binarization first and then skeletonization), in that it can overcome the problem that some separate vein lines are extracted incorrectly, and it can avoid extracting two neighboring vein lines as one ridge. As such, the proposed method is an effective way to extract topographic features for vein recognition.