A novel finger vein feature extraction technique for authentication

Biometrics is mainly used for human identification using different physical traits. The traits that can be used as biometrics are face, palm print, voice, signature, gait etc. But use of these traits in biometrics is not perfectly reliable or secure. So, in order to overcome the security issue, a non-forgeable pattern has to be used. In terms of security and convenience, the finger-vein is a promising biometric pattern for human identification. Since the vein images can be taken from live body only and these patterns being attributes present inside the human body, they are extremely complex to forge. In this paper, the finger vein images are enhanced by incorporating the concept of local histogram equalization, which improves the local contrast of an image. The features are extracted from the enhanced images using a combination of Frangi filter, FAST(Features from Accelerated Segment Test) algorithm and FREAK (Fast Retina Keypoint) descriptors.