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Directional Connected Components Algorithm Based on Gradient Information

机译:基于梯度信息的定向连通分量算法

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This paper presents a directional connected components algorithm that overcomes the problem of overlapping components by gradient information. The proposed algorithm replaces the binary matrix with the directional matrix that contains the gradient information. The directional matrix contains both the gradient magnitude and angle and provides the merge decisions of neighboring pixels for solving the problem of overlapping edges. The proposed algorithm improves the performance of the connected components algorithm in the classification of features and candidates using edge information. Experimental results demonstrate that the proposed algorithm can resolve the problem of overlapping components, and prevent false connections between components and background under various circumstances.
机译:本文提出了一种有向连通分量算法,该算法克服了梯度信息重叠分量的问题。该算法将二进制矩阵替换为包含梯度信息的方向矩阵。方向矩阵既包含梯度量值又包含角度,并提供相邻像素的合并决策,以解决重叠边缘的问题。所提出的算法在使用边缘信息对特征和候选进行分类的过程中提高了连通分量算法的性能。实验结果表明,该算法能够解决部件重叠的问题,并能在各种情况下防止部件与背景之间的虚假连接。

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