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A new corner detection algorithm for chain code representation

机译:一种新的用于角码表示的角点检测算法

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摘要

A new algorithm is proposed to detect a corner of a thinned binary image that is represented by an eight-connected contour chain code. The algorithm is based on chain-coded image, deriving the slope between each code, analyze the series of chain code, and finally decide the existence of corner at the current pixel location. The work assumes that the pre-processing processes on the image, namely thinning and digitization, have been done. Two weighted parameters identified as significant factors in determining the accuracy of the corner detection algorithm are discussed. The parameters are the length of segment and threshold value. Computational phases to derive values of rows and columns given a series of chain code are also given in detail. The algorithm can be used to interpret line drawing that represents three-dimensional object.
机译:提出了一种新算法来检测由八联轮廓线代码表示的稀疏二进制图像的拐角。该算法基于链编码图像,推导每个编码之间的斜率,分析一系列链编码,最后确定当前像素位置是否存在拐角。这项工作假设图像的预处理过程已经完成,即细化和数字化。讨论了确定为角点检测算法准确性的重要因素的两个加权参数。参数是段的长度和阈值。还详细给出了在给出一系列链码的情况下得出行和列的值的计算阶段。该算法可用于解释代表三维对象的线图。

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