Reducing circular hough transform parameters using morphological operations
Alireza Bosaghzadeh · 2017
This article introduces a new technique to reduce the parameters of the Circular Hough Transform (CHT). CHT is a well-known technique to locate circles in an image. One of the main drawbacks of CHT is its three-dimensional parameter space (location and radius of the circle) which makes this algorithm not memory efficient. In this article, based on morphological operations, we reduce this parameter space to two parameters which greatly improves its speed and memory. In the first step, we determine the radius of the circles using morphological operations. In the second step, only the location of the circle centers should be found. This trick will reduce the need for a third parameter of the CHT, hence can greatly reduce the consumed memory. Moreover, by using morphologically processed images, the images that we feed to CHT mainly have circles with a specific radius while most of other objects are removed. This trick improves the speed of the algorithm since the number of false edges is greatly reduced. Experimental results on different images prove that the proposed method can detect circles with a two-dimensional accumulator space.