Human identification system using finger vein images

In this thesis a human identification using finger vein image with local binary pattern is presented. Human identification with its high safety performance became famous in many security devices. Finger vein identifying technique has become the most preferred because it's low device restrictions and avoid forgery. In this study of advancement in human identification using finger vein image with binary pattern is given. Generally it focused on several aspects. First, finger vein identification system will be presented. Also the methods have been used for extracting features of the vein will be shown. Finally the local binary pattern useded for the propose of this project. In this thesis, presented a robust method for finger vein recognition with gray level co- occurrence matrix based on the discrete wavelet transform. In first step for compression of the image we used wavelet Daubechies 4. Also we used local binary pattern for feature extraction. The combination of local binary pattern (LBP) and gray level co- occurrence matrix (GLCM) with discrete wavelet transform (DWT) is not used before for finger vein recognition. The simulation results showed that this method is robust and fast for feature extraction and classification. With this newly developed method, we improved the performance of the wavelet transform system and compressed the image by 2 times. By reducing the size of the image, we have made algoloritman fast and responsive. Simulation results show that this method is robust and fast for feature extraction and classification. SDUMLA-HMT and MMCBNU-6OO6 for data analysis and calculations, Data Bank of SouthKoreo State-Chonbuk State University 1000 different human finger image systems were used. All simulations in the draft Calculations MatLAB-2016 Program has been analyzed within the framework of error limits.