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An Improved Algorithm of Hand Gesture Recognition under Intricate Background

机译:复杂背景下的手势识别的改进算法

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This paper presents an integrated algorithm of YCbCr-Nrg, Double Color-Spatial Model and Background Model to resolve the problem that single skin-color model is obstructed by near kin color. This segmentation method is realized by the fusion of multi-feature. Based on the good describing ability of Fourier Descriptors algorithm and the good self-learning ability of BP neural network, an improved algorithm of hand recognition is presented and carried out. Results show that this algorithm is robustness for hand gesture recognition under intricate background.
机译:本文介绍了YCBCR-NRG,双色空间模型和背景模型的集成算法,以解决单一肤色模型靠近亲属遮挡的问题。通过多特征的融合来实现该分段方法。基于傅立叶描述符算法的良好描述能力和BP神经网络的良好自学习能力,提出和执行了一种改进的手识别算法。结果表明,该算法在复杂背景下的手势识别是手势识别的鲁棒性。

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