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The Application of Randomized Hough Transform in Ellipse Image Detection

机译:随机Hough变换在椭圆图像检测中的应用

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As the traditional Hough transform has such defects as large storage space and long computing time in ellipse detection, an improved randomized ellipses detection method based on least squares was presented, which utilizes the least square approach to fit the ellipse and combines both of the advantages of the random Hough transform and the least square. By setting appropriate distance threshold of the candidate ellipse and the threshold of edge points, the method of ellipse detection decreases the number of random sampling and the invalid calculation of cumulation in the process of Hough transform. The results show that the method doesn't require large storage space, has good ability to overcome the noise and realizes the fast detection for the single ellipse and defective ellipse.
机译:由于传统的霍夫变换具有大存储空间和椭圆检测中的长计算时间的这种缺陷,提出了一种基于最小二乘的改进的随机椭圆检测方法,利用最小二乘方法来适应椭圆并结合其两个优点。随机霍夫变换和最小二乘。通过设置候选椭圆的适当距离阈值和边缘点的阈值,椭圆检测方法减少了霍夫变换过程中的随机采样的数量和无效计算。结果表明,该方法不需要大的存储空间,具有良好的克服噪声的能力,实现单个椭圆和缺陷椭圆的快速检测。

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