Circle Detection in MATLAB Environment

Resource Overview

Detecting circles in MATLAB typically involves processing binary images after binarization, for example using edge detectors. Standard functions usually require specifying the exact circle radius. The circle_hough function enables circle detection by specifying a range of radii, eliminating the need for precise prior knowledge of the radius. This approach can be faster than repeatedly calling standard functions with different radii. The algorithm can detect multiple circles by finding peaks in a 3D accumulator array, with circle_houghpeaks function provided for peak detection and circle parameter extraction.

Detailed Documentation

In the MATLAB environment, circle detection in images can be performed using methods like edge detectors after image binarization. Typically, standard circle detection functions require specifying the exact radius of the circles.

The circle_hough function provides more flexible functionality by allowing specification of a radius range, eliminating the need for precise prior knowledge of the radius. This implementation uses the Hough transform algorithm for circles, which can be more efficient than repeatedly calling standard functions with different radii. The function works by creating a 3D accumulator array that accumulates votes for potential circle centers and radii, enabling detection of multiple circles through peak finding in this parameter space.

Additionally, the circle_houghpeaks function is provided for post-processing the accumulator array to identify and extract parameters of detected circles. This function implements peak detection algorithms to locate local maxima in the Hough space, corresponding to detected circles in the image.