False circle detection algorithm based on Minimum Support Percentage and Euclidean Distance

Circle detection over digital images has received considerable attention from the computer vision community over the last few years devoting a tremendous amount of research seeking for an optimal detector. Circle detection algorithms which were proposed till now have some limitations. One major limitation is detection of false circles in image. An efficient method of detecting false circles, called False Circles Detection Algorithm (FCDA) based on Minimum Support Percentage (MSP) and Euclidean Distance is presented. The proposed algorithm can be used along with the existing algorithms giving better results. Experimental results over some real industrial images show that the proposed algorithm is efficient in terms of accurate detection.