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Hand shape based gesture recognition in hardware

机译:硬件中基于手形的手势识别

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It is possible to recognize and classify ten hand gestures based solely on their shapes. This paper discusses a simple recognition algorithm that uses three shape-based features of a hand to identify what gesture it is conveying. The overall algorithm has three main steps: segmentation, feature calculation, and classification. The algorithm takes an input image of a hand gesture and calculates three features of the image, two based on compactness, and one based on radial distance. The parameters found in the classification step were obtained empirically using 200 hand images. The algorithm was tested on another 200 hand images, and was able to successfully classify 182 images, or with an overall success rate of 91 percent.
机译:可以仅根据手势的形状来识别和分类十个手势。本文讨论了一种简单的识别算法,该算法使用手的三个基于形状的特征来识别其传达的手势。总体算法包括三个主要步骤:分割,特征计算和分类。该算法获取手势的输入图像,并计算图像的三个特征,其中两个基于紧凑度,一个基于径向距离。使用200张手部图像凭经验获得在分类步骤中找到的参数。该算法在另外200张手形图像上进行了测试,能够成功分类182张图像,总成功率为91%。

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