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Design of a hand-shape acquisition and recognition system based on DSP

机译:基于DSP的手形采集与识别系统的设计

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In this paper, we design a hand-shape image acquisition and processing system based on DSP for solving the problem of hand-shape recognition. Acquisition configuration was designed, and the key parts (encoder, decoder, memory chip etc.) are selected. And a new method for hand-shape recognition based on wavelet moment is presented to overcome some shortage in present method for hand shape recognition. Firstly, image processing including binary processing and segment of hand silhouette are used, and then translation and scale normalization algorithms is implemented on the palms and fingers image. After that the wavelet moment characteristics of image are extracted. At last, support vector is achieved by training 100 images data in images database, 10 testing images were selected randomly to verify validity and feasibility of algorithms. Experimental results indicate that the 10 testing images are all classified correctly. The new method of extracting hand shape wavelet moment as characteristic matrix is easy to realize with characteristic of high utility and accuracy, and solve the problem of translation, rotation and scaling during the image acquisition process without positioning aids.
机译:在本文中,我们设计了一种基于DSP的手形图像采集和处理系统,用于解决手形识别问题。设计采集配置,选择关键部件(编码器,解码器,存储器芯片等)。基于小波力矩的手工形状识别方法,以克服现有方法的手工形状识别的一些短缺。首先,使用包括二进制处理的图像处理和手剪影的段,然后在手掌和手指图像上实现平移和比例归一化算法。之后提取图像的小波矩特性。最后,通过在图像数据库中训练100个图像数据来实现支持向量,随机选择10个测试图像以验证算法的有效性和可行性。实验结果表明,10个测试图像全部分类。提取手形小波矩作为特征矩阵的新方法易于实现高效用和精度的特性,并解决图像采集过程中的翻译,旋转和缩放问题而不定位辅助工具。

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