The Research Based On Authentication Technology Of Finger Vein

With the development of the information security requirement of modern society, using biometric character to identify one's identification quickly and exactly thrives. Vein Pattern Recognition is a new contactless biometric technology using IR. It not only offers high accuracy personal identification, but also offers high safety, usability, and can be implemented easily. So it becomes a hot spot stage by stage. According to the characteristic of the infrared light that while the infrared light is absorbed intensively by the blood, it is dispersed by other organs of the body. The finger vein recognition technology is carried on the body's identification through the finger vein. Based on the latest extensive discourses and technology journals in this field, the dissertation is trying to make studies on finger vein recognition.The finger vein image pre-processing, minutiae extracting and matching is mainly studied in the dissertation. The simulation is complemented by MATLAB 7.0 on PC and the finger vein identification system is designed at last. The contents are as follows:Firstly, the finger vein image is dealt with the image pre-processing technologies. Pre-processing technologies includes edge location, normalization, filter and Histogram Modification. Its purpose is to remove noise of vein image and improving definition of vein image, which will be beneficial to following feature extraction.Secondly, the features are extracted from the finger vein image. The features of finger vein's topology which means skeleton features are mainly extracted. Based on the analysis of traditional means of segmentation, due to the fact that the algorithm is time-consuming, with low accuracy rate, the dissertation proposes a novel algorithm for finger vein's skeleton features extraction which can remove interference effectively and improve the speed rapidly. With multi-scale Morphological transform, the images will be scanned across the edges and the valley detection will be done from the four directions. So, the shortcomings of the methods which compare the intensities pixel by pixel are avoided. Experimental results have proved that the finger vein extracted by the proposed method has more precise details and better continuity. The running time is reduced too.Thirdly, the search on recognition algorithm of finger vein images is implemented. In this dissertation, we implement two recognition algorithms, that is, based on Hu moment invariants and Tchebichef orthogonal moment invariants, with the nearest neighbor feature, and based on BP neural network. Against the low identification rate of the former algorithm, geometry in topology and moment features are used as input vector in BP neural network. Experiments have proved that the matching method based on BP neural network achieved good results on both speed and recognition rate.Finally, the finger vein identification system is designed. The hardware includes infrared LED, CMOS image sensor which is used for image acquisition and ADSP BF561 which is used to realize algorithm.