Finger Vein verification using local histogram of hybrid texture descriptors

Lately, finger vein has been recognized as an efficacious biometric method for user authentication due to the uniqueness of vein patterns and its insusceptibility to forgery because the vein patterns reside inside the human body. In this work, hybrid histogram descriptor is the proposed method. This method utilizes the sign and magnitude components of the texture extracted by using Binary Gradient Contour (BGC). Subsequently, the histogram is locally computed to determine the weight distribution of the sign and magnitude value for the hybrid texture descriptors. The extensive experimental results demonstrate the overall superiority of the proposed method with the EER as low as 0.353%.