Abstract
The detection of circles from digital images is very important to shape recognition. In this paper, we propose and analyze a novel method, based on power histograms to detect circles in an image. The key idea is to transform an image into several power histograms that are computed from the pairwise distance products referring to the rays emanated from some reference points on the image. According to the circle power theorem, the edge pixels on a circle share the same circle powers with respect to an arbitrary point on the image. The peaks in the power histograms provide strong evidence for the existence of real circles. A multi-reference cross validation among various peaks can systematically remove randomness and eliminate false detections. Experimental results over several synthetic as well as natural images with varying ranges of complexity validate the efficacy of the proposed method in terms of its accuracy, simplicity, and robustness.
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