Affiliations: [a]
School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China
| [b] GuangZhou Huan Tek Co., Ltd, Guangzhou, China
| [c]
China Information and Communication Research Institute, China
Correspondence:
[*]
Corresponding author. Zhiheng Zhou, School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510640, China. E-mail: [email protected].
Abstract: A new algorithm for static hand gesture recognition is proposed in this paper, which mainly includes the following four steps: hand segmentation, arm removal, feature extraction and gesture recognition. Firstly, the hand is extracted from the background by using skin-color features and geometric characteristics. Secondly, a new arm removal algorithm is proposed, which can effectively and quickly remove the arm area by using distance transformation operations, and gesture composed of palm and fingers can be obtained. Finally, Hu moments of the gesture image and the number of fingertips are calculated and entered into the Support Vector Machine (SVM) for training. Experiments have been performed to demonstrate that the proposed algorithm is robust in complex background, and can detect and recognize gestures in real time with an accuracy of 94.89%.
Keywords: Arm removal, static hand gesture recognition, distance transformation, SVM
