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The method based on boundary chain-code for objects recognition and gesture analysis

机译:基于边界链码的目标识别与手势分析方法

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Chain-code has been shown to be efficient and effective for describing objects in image. Based on the boundary chain-code, we present a method for object recognition. Firstly, we propose a novel method to form a closed contour and convert the chain-code into an ordered array and then transfer it to the frequency domain. Changing the start point of the chain-code, it shows that the amplitude distributions in the frequency domain is kept invariant. Secondly, the features of the amplitude distribution with the changing boundary scale and the adding noises are introduced. Finally, the experiment results have been given to illustrate the validity on the object recognition with the character of the amplitude distributions, while altering the start point of the chain-code and changing the object contour slightly. In addition, the gesture of human motion is analyzed.
机译:链码已被证明对于描述图像中的物体非常有效。基于边界链代码,我们提出了一种物体识别方法。首先,我们提出了一种新颖的方法来形成闭合轮廓,并将链码转换为有序数组,然后将其传输到频域。改变链码的起点,它表明频域中的幅度分布保持不变。其次,介绍了随着边界尺度变化和噪声增加而出现的振幅分布特征。最后,给出了实验结果,以振幅分布的特征说明了目标识别的有效性,同时改变了链码的起始点,并略微改变了目标轮廓。另外,分析了人类动作的姿势。

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