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Max-min hand cropping method for robust hand region extraction in the image-based hand gesture recognition

机译:基于图像的手势识别中鲁棒手区域提取的最大-最小手裁剪方法

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摘要

There have been many developments and applications based on hand posture recognition to make human-computer interaction/interfaces more convenient and effective. And, many of these applications are based on the image-processing technique since it can guarantee more information and more flexibility for processing. To develop a hand posture recognition system, the proper extraction of pure hand region is a very important step since it is much related with the final performance and recognition rate. But, by the noisy data due to the illumination, image resolution, and non-uniform distribution of skin colors which could be easily found in real environments, it is not easy to extract the pure hand region exactly. In this research, a simple and effective algorithm for hand cropping, named as max-min hand cropping, is proposed and compared with some of the previous research. Finally, the effectiveness of the proposed method is verified with 152 different hand images from 8 persons and 19 hand postures.
机译:基于手势识别的许多开发和应用使人机交互/界面更加方便和有效。并且,这些应用中的许多基于图像处理技术,因为它可以保证更多的信息和更大的处理灵活性。要开发手势识别系统,正确提取纯手区域是非常重要的一步,因为它与最终性能和识别率密切相关。但是,由于照明,图像分辨率和肤色的不均匀分布(在实际环境中很容易找到)而产生的嘈杂数据,要准确地提取纯手区域并不容易。在这项研究中,提出了一种简单有效的手部裁剪算法,即max-min手部裁剪,并与以前的一些研究进行了比较。最后,该方法的有效性通过来自8个人和19种手势的152种不同的手部图像进行了验证。

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