ROI extraction for online touchless palm vein based on concavity analysis

Region of Interest extraction is the crucial step in palm vein recognition, which is quite important for the subsequent feature extraction and recognition. In this paper, we propose a novel ROI extraction method which is robust to the effect of scaling, rotation and irregular boundary. It constructs a down-sampling method for the boundary approximation and presents a novel concavity analysis model to extract the ROI with high success rate. Moreover, this paper uses the distance extension factors to extend the normal ROI extraction and obtain an information-richer region. Example results on the PolyU palm vein database and CASIA database indicate that the proposed ROI extraction method gives a superior performance as compared to the previously proposed point-based approaches.