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An improved generalized Hough transform for the recognition of overlapping objects

机译:一种改进的广义Hough变换,用于识别重叠对象

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The generalized Hough transform (GHT) is a powerful method for recognizing arbitrary shapes as long as the correct match accounts for both much of the model and much of the sensory object. For moderate levels of occlusion, however, the GHT can hypothesize many false solutions. In this paper, we present an improved two-stage GHT procedure for the recognition of overlapping objects. Each boundary point in the image is described by three features including the concavity, radius and norml direction of the curve segment in the neighborhood of the pint.
机译:广义霍夫变换(GHT)是一种识别任意形状的有效方法,只要正确的匹配既能说明模型的大部分内容,又能说明感官对象的大部分内容。但是,对于中等水平的遮挡,GHT可以假设许多错误的解决方案。在本文中,我们提出了一种改进的两阶段GHT程序,用于识别重叠物体。图像中的每个边界点都由三个特征来描述,包括品脱附近曲线段的凹度,半径和范数方向。

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