Finger-vein image separation algorithms and realization with MATLAB

According to the characteristics of the finger-vein image, we adopted a series of methods to enhance the contrast of the image in order to separate the finger-vein areas from the background areas, and made prepare for the subsequent research such as feature extraction and recognition processing . The method consists of three steps: denoising, contrast enhancement and image binarization. In denoising, considering the relationship between gray levels in the adjacent areas of the finger-vein image, we adopted the Gradient Inverse Weighted Smoothing method. In contrast enhancement, we improved the conventional High Frequency Stress Filtering method and adopted a method which combined the traditional High Frequency Stress Filtering algorithm together with the Histogram Equalization. With this method, the contrast of the finger-vein area and the background area has been enhanced significantly. During the binarization process, after taking the differences of the gray levels between the different areas of the finger-vein image into consideration, we proposed a method which combined the binarization by dividing the image into several segments and the Morphological Image Processing means. Our experiment results show that after a series of processing mentioned above by using MATLAB, the finger-vein areas can be separated from the background areas obviously. We can get a vivid figure of the finger-vein which provided some references for the following research such as finger-vein image feature extraction, matching and identification.