Detecting circles from a digital image is very important in shape recogniti
on. In this paper, an efficient randomized algorithm (RCD) for detecting ci
rcles is presented, which is not based on the Hough transform (HT). Instead
of using an accumulator for saving the information of the related paramete
rs in the HT-based methods, the proposed RCD does not need an accumulator.
The main concept used in the proposed RCD is that we first randomly select
four edge pixels in the image and define a distance criterion to determine
whether there is a possible circle in the image: after finding a possible c
ircle, we apply an evidence-collecting process to further determine whether
the possible circle is a true circle or not. Some synthetic images with di
fferent levels of noises and some realistic images containing circular obje
cts with some occluded circles and missing edges have been taken to test th
e performance. Experimental results demonstrate that the proposed RCD is fa
ster than other HT-based methods for the noise level between the light leve
l and the modest level. For a heavy noise level, the randomized HT could be
faster than the proposed RCD, but at the expense of massive memory require
ments. (C) 2001 Academic Press.