Abstract

Circle detection is an important issue that has not been perfectly solved in automated image analysis to date. It is traditionally carried out via pixel-based 3D voting algorithms, involving tremendous computation and requiring huge storage space with questionable accuracy. In this report, a novel edge-section-based 1D voting algorithm is developed in circle detection to improve the detection rate and precision. Based on experiments with simulated image data and a ground-tested standard dataset, the novel scheme significantly outperformed all previous state-of-the-art schemes in detection rate and precision, and was comparable to the state of the art in processing speed.

© 2014 Optical Society of America

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