一种基于肤色特征提取的手势检测识别方法

Research on hand gesture detection and recognition method based on skin color feature extraction

针对手势识别的准确率和识别速度等问题,提出一种基于肤色特征提取的手势检测识别方法。采用OpenCV自有的Haar分类器自动提取面部区域并建立肤色模型,再以肤色模型检测肤色点集合,去除与面部区域重合点集获得手部轮廓,通过综合计算掌心位置,手掌轮廓凸包和凸性缺陷实现手势识别。经验证,该方法能够稳定地定位手掌区域,识别准确度高并能够在保证识别率的基础上实现对手势的快速识别。

Aiming at the low recognition accuracy and slow recognition speed for hand gesture, a hand gesture detection and recognition method based on skin color feature extraction is proposed. The Haar classifier owned by OpenCV itself is used to extract face regions automatically and establish skin color model; and the skin color model is adopted to detect the point sets of skin color, in which the point set overlapped with face area is removed to acquire the hand contour; then the location of palm center is calculated comprehensively to detect the convex hull and convexity defect of palm contour to recognize the hand ges- ture. The verification results show that the method can locate the palm area accurately and realize fast recognition for hand ges- ture while ensuring the recognition rate, and its recognition accuracy is high.