Extraction of dorsal palm basilic and cephalic hand vein features for human authentication system

• Published in: 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) pp. 2231 - 2235
• Main Authors: Sandhiya, D., Thiyaneswaran, B.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2017
• Subjects: Authentication; Conferences; edge detection; Feature extraction; GLCM; Image edge detection; Image segmentation; k-Means; Median filter; Skin; Vein patterns; Veins
• DOI: 10.1109/WiSPNET.2017.8300156

A human authentication in now a day is based on biometrie system. A hand vein biometrics is the upcoming technology. It has higher advantages than the existing biometrics. The hand vein consists of forearm wrist veins, palm veins, finger veins, and anterior positions. The proposed work extracts the dorsal palm vein features. The proposed system uses the hand vein capturing system. The focusing is based IR LED with 760 nm wavelength. The IR focusing system is placed inside the wooden box. The camera is used to capture the image. The captured RGB image is converted into HSV format. The hue, saturation, and brightness components are separated. An illumination correction is applied on the brightness component. The veins are segmented from the dorsal palm using k-means clustering. The GLCM features are extracted from the veins and taken as one part of the feature. Preprocessing steps such as median filter, binary conversion, image complement, and canny edge detection are applied on the captured image. The vein feature points are located in the captured image.