Circular hole detection algorithm based on image block

Abstract

Circular hole detection is a common problem in computer vision and pattern recognition. Randomized Hough transform and randomized circle detection algorithm are commonly used in circle detection, with good detection robustness and accuracy. But for circular holes with smaller radius, the two algorithms will be too slow because of a large number of invalid sampling. Thus the circular hole detection algorithm based on image block is proposed in order to improve the speed of circular hole detection. The algorithm divides the image into several small blocks and 3 points from the same block are randomly selected for sampling each time. If a candidate circular hole can be obtained by calculating these 3 points, then the points in the 4 blocks (or less) closest to the center of the candidate hole will be used for evidence-collecting to determine whether the candidate circular hole is true. Experimental results on a large number of synthetic images and real images show that the detection speed of circular hole detection algorithm proposed is much faster than the speed of randomized Hough transform and randomized circle detection algorithm. In addition, the proposed algorithm has the same detection robustness and accuracy as the randomized circle detection algorithm. The block strategy proposed in this paper is also applicable to the detection of elliptical holes.