Hand vein recognition with rotation feature matching based on fuzzy algorithm

Document Type : Research Paper

Authors

1 Business Information Technology Department, Business Informatics College, University of Information Technology and Communications, Baghdad, Iraq.

2 Bioinformatics Department, BioMedical Informatics College, University of Information Technology and Communications, Baghdad, Iraq.

Abstract

The Bodily motion or emotion, which can be obtained for example from a hand or a face, originates gestures. Every individual has a unique pattern of dorsal hand veins. The vein pattern's orientation changes when one rotates their hand in a particular direction. This study focused on hand-gesture recognition using dorsal hand veins. The aim of this work is a novel technique to track and recognizing hand vein rotation using fuzzy neural network, and the change in orientation was considered as a gesture and measured.  The algorithms were tested over various rotations ranging from $-45^{\circ}$ to $+45^{\circ}$. We successfully detected various rotations in both clockwise and anti-clockwise directions, achieving $93\%$ accuracy and a reasonable time execution. This problem can be solved because a person can steer a car wheel merely by rotating his/her hand. An infrared camera captured the rotation of hand veins, so car wheel steering was unnecessary.

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