Using Image Processing to Performing Biometric Authentication Applied on Microcomputer Based Hand-Wrist Vein Patterns

Abstract

A kind of biometric recognition called vein identification systems uses vascular architecture to identify people. One of these approaches is identification based on hand-wrist vein pattern. Hand-wrist vein pictures acquired from persons utilizing an infrared light source with a wavelength of 850 nm were segmented in this research by running them through several image processing techniques. The scale-independent feature transformation (SURF) approach was used to extract critical points from segmented pictures. The SURF approach produces characteristics such as rotation, camera angle, ambient light intensity, and so on. This strategy has been chosen since it is unaffected by circumstances. During the identification procedure, the retrieved key points were utilized to calculate the Euclidean distance. The accuracy rate was judged to be 97% as a consequence of the matching operations employing the database's hand-wrist vein patterns.