Circle detection based on hough transform and Mexican Hat filter

Nova Hadi Lestriandoko, Rifki Sadikin
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引用次数: 24

Abstract

Circles detection is an important part of object recognition in image processing and computer vision. In this paper, we propose an adaptive method based on Hough transform to detect the circle shapes in digital image. The Mexican Hat filter derived from edge filter is used to concentrate the peaks of Hough local maxima. So, the circle center and its radius can be extracted easily and accurate. The comparison of adaptive method and traditional Hough transform will be analyzed. Experimental results over several digital images with varying ranges of complexity showed the efficiency of proposed method that more efficient than traditional Hough transform. Finally, The development of circles detection is still needed to get the best results, especially for circles shape with any noise.
基于霍夫变换和墨西哥帽滤波的圆检测
圆检测是图像处理和计算机视觉中目标识别的重要组成部分。本文提出了一种基于霍夫变换的自适应圆形图像检测方法。利用由边缘滤波器衍生而来的墨西哥帽滤波器对霍夫局部极大值的峰值进行集中。因此,可以方便、准确地提取圆心和半径。分析了自适应方法与传统霍夫变换的比较。在不同复杂度范围的数字图像上的实验结果表明,该方法比传统的霍夫变换更有效。最后,为了获得最佳的检测效果,特别是对于带有噪声的圆形,还需要进一步发展圆检测技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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