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An Improved Hough Transform for Circle Detection using Circular Inscribed Direct Triangle

机译:一种改进的霍夫变换,用于使用圆形内接直接三角形的圆检测

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Considering that the classical Hough transform for circle detection has poor real-time performance because of massive computation and memory consumption caused by accumulative voting in three-dimensional parameter space, this paper presents an improved Hough circle detection algorithm using circular inscribed direct triangle. The algorithm reduces the three-dimensional parameter space needed by classical Hough transform to two-dimensional parameter space by utilizing the geometrical characteristics of circle. By traversing an s pixels only once, the coordinate points which may be centers of candidate circles are voted, and the radius corresponding to the coordinate points whose number of votes exceeds the user-defined threshold is taken out. Finally, the false circles are eliminated, and all real circles in the image are detected. The experimental results show the algorithm has fast speed, high accuracy and good anti-noise performance in contrast with the classical Hough circle detection method.
机译:考虑到传统的霍夫变换用于圆检测的实时性较差,因为在三维参数空间中累积投票会导致大量计算和内存消耗,因此,本文提出了一种改进的基于圆形内接直接三角形的霍夫圆检测算法。该算法利用圆的几何特征将经典霍夫变换所需的三维参数空间减少为二维参数空间。通过仅遍历s个像素一次,对可能是候选圆心的坐标点进行投票,并取出与投票数超过用户定义的阈值的坐标点相对应的半径。最后,消除假圆,并检测图像中的所有实圆。实验结果表明,与传统的霍夫圆检测方法相比,该算法具有速度快,精度高,抗噪性能好等优点。

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