hand vein recognition with rotation feature matching based on fuzzy algorithm

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◦ to +45◦. 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.