Description

Authentication one of the research area in recent year. There are so many authentication method is there like software, hardware, and biometric the biometric authentication system is one of best authentication process. The biometric system will help to improve the security. The biometric details of the each person is unique. In that reasons the biometric is like Individual password of each person. It is not use by another person and not easily to hack. In our proposed authenticate the person based on the biometric details of finger knuckle texture and vein. The finger knuckle is unique of every person the finger vein is also change in every person. In our proposed we extract the feature of finger knuckle and finger vein by using Local binary pattern and 1-D Gabor filter. The local binary pattern generate the pattern for identify the pixel information of the image. That local variant patterns crate by the intensity value of the image by setting the thresh hold to identify the pixel change in nearest pixels of image. The local binary pattern extract the binary value by based on the thresh hold of nearest pixels and convert to the decimal it give information about the image intensity values. The 1D Gabor filter is the best algorithm to extract the features values of selected image. K-nearest neighbor classifier will classify the features by best accuracy, sensitivity and low error rate. That all above methods will improve our authentication quality.