A new curve detection method: randomized Hough transform (RHT)
Pattern Recognition Letters
Comparative study of Hough transform methods for circle finding
Image and Vision Computing - Special issue: 5th Alvey vision meeting
Parallel simulated annealing for shape detection
Computer Vision and Image Understanding
Deriving stopping rules for the probabilistic Hough transform by sequential analysis
Computer Vision and Image Understanding
A linear algorithm for incremental digital display of circular arcs
Communications of the ACM
Shape Analysis and Classification: Theory and Practice
Shape Analysis and Classification: Theory and Practice
An efficient randomized algorithm for detecting circles
Computer Vision and Image Understanding
Geometric Primitive Extraction Using a Genetic Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Circle detection on images using genetic algorithms
Pattern Recognition Letters
An Efficient Ellipse-Drawing Algorithm
IEEE Computer Graphics and Applications
Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing
Computer Communications
Performance evaluation of memetic approaches in 3D reconstruction of forensic objects
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Emerging Trends in Soft Computing - Memetic Algorithms; Guest Editors: Yew-Soon Ong, Meng-Hiot Lim, Ferrante Neri, Hisao Ishibuchi
Automatic circle detection on digital images with an adaptive bacterial foraging algorithm
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Expert Systems with Applications: An International Journal
Circle detection using discrete differential evolution optimization
Pattern Analysis & Applications
EDCircles: A real-time circle detector with a false detection control
Pattern Recognition
Block-matching algorithm based on harmony search optimization for motion estimation
Applied Intelligence
Multi-circle detection on images inspired by collective animal behavior
Applied Intelligence
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Automatic circle detection in digital images has received considerable attention over the last years in computer vision as several novel efforts aim for an optimal circle detector. This paper presents an algorithm for automatic detection of circular shapes considering the overall process as an optimization problem. The approach is based on the Harmony Search Algorithm (HSA), a derivative free meta-heuristic optimization algorithm inspired by musicians improvising new harmonies while playing. The algorithm uses the encoding of three points as candidate circles (harmonies) over the edge-only image. An objective function evaluates (harmony quality) if such candidate circles are actually present in the edge image. Guided by the values of this objective function, the set of encoded candidate circles are evolved using the HSA so that they can fit into the actual circles on the edge map of the image (optimal harmony). Experimental results from several tests on synthetic and natural images with a varying complexity range have been included to validate the efficiency of the proposed technique regarding accuracy, speed and robustness.