文件名称:1-LEd
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现在，基于视觉的手势识别中起着重要的在图像处理领域的作用，模式识别等在。人类的手是高度可变的器官和手特点是很容易受到各种环境因素的影响。考虑到手势的特性，在本文中我们提出了一种改进的YCbCr颜色空间的分割方法手势图像，并提取傅里叶描述子和胡矩作为识别特征。最后，Hausdorff距离用于识别手势的建模方法匹配。实验结果表明，提出的方法具有较高的操作和识别率。
关键词：-Now vision-based gesture recognition plays an important
role in the filds of image processing, pattern recognition and so
on. Human being hands are highly variable organs and hand
features are affected easily by various environmental factors.
Considering the characteristics of hand gesture, in this paper we
proposes an improved YCbCr color space method to segment
gesture images, and extracts Fourier descr iptors and Hu
moment as recognition features. Finally, the Hausdorff distance
is applied to recogniz the gestures by the method of model
matching. Experimental results show that the proposed method
has higher operation and recognition rates.
关键词：-Now vision-based gesture recognition plays an important
role in the filds of image processing, pattern recognition and so
on. Human being hands are highly variable organs and hand
features are affected easily by various environmental factors.
Considering the characteristics of hand gesture, in this paper we
proposes an improved YCbCr color space method to segment
gesture images, and extracts Fourier descr iptors and Hu
moment as recognition features. Finally, the Hausdorff distance
is applied to recogniz the gestures by the method of model
matching. Experimental results show that the proposed method
has higher operation and recognition rates.
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