Circle detection based on hough transform and Mexican Hat filter
Nova Hadi Lestriandoko, Rifki Sadikin · 2016
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.