Region of Interest Extraction for Finger Vein Images with Less Information Losses.

Automatic finger vein recognition systems have attracted more attentions in recent years. In order to implement a high performance system, an important step is to localize the region of interest accurately. A problem in previous ROI localization methods is that some useful finger vein information is lost in the final cropped ROI region. In order to resolve this problem, a novel ROI extraction method for finger vein images is proposed in this paper. Finger edges are detected and adjusted to the horizontal direction, after that a modified sliding window is used in order to detect the distal inter-joint line of the finger. On the basis of the edges and the distal inter-phalangeal joint line of the finger, different from previous methods, an outer rectangle is used to crop the finger area to avoid the useful information loss. Based on our experimental dataset with 3132 finger vein images, the mean information loss rate for previous methods is 15.1% and there is no loss of information for our method. In order to evaluate the accuracy of our ROI extraction method, the similarity rate of intra-class is calculated, which is defined by the ratio of overlap area and the whole ROI area. And a mean similarity rate 96.3% is obtained in our experiments. Theoretical analysis and experimental results show that the proposed method is effective and accurate, and it is potentially beneficial for improving the performance of finger vein recognition system.