Abstract
In this paper, a new recognition algorithm was developed based on the skin color model and the fingertip structure detection to improve the hand gesture recognition accuracy based on the traditional Hu's moment features. Firstly, the geometric features and the areas of skin were adopted to segment the skin region from the background. The Douglas–Peucker (D–P) algorithm was utilized to conduct the contour approximation to get a polygonal in the process of feature detection. Then the convexity point inspections were conducted in the polygonal. Secondly, we developed two rules for locating and numbering the fingertips. After that, we built a seven-dimensional feature vector. Finally, the hand gesture was recognized by using the distance matching criterion. The developed recognition algorithm improved the recognition accuracy by 2.7% compared with the traditional Hu's moment features. Additionally, it has good robustness in several manners such as shifting, plane rotation and scaling.
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