Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
A new curve detection method: randomized Hough transform (RHT)
Pattern Recognition Letters
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
Circle detection on images using genetic algorithms
Pattern Recognition Letters
An Efficient Ellipse-Drawing Algorithm
IEEE Computer Graphics and Applications
Particle swarm optimization with adaptive population size and its application
Applied Soft Computing
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
Nature-Inspired Metaheuristic Algorithms
Nature-Inspired Metaheuristic Algorithms
Predication based immune network for multimodal function optimization
Engineering Applications of Artificial Intelligence
Automatic circle detection on digital images with an adaptive bacterial foraging algorithm
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Circle detection using discrete differential evolution optimization
Pattern Analysis & Applications
Circle detection using electro-magnetism optimization
Information Sciences: an International Journal
Psychological model of particle swarm optimization based multiple emotions
Applied Intelligence
Circle Detection by Harmony Search Optimization
Journal of Intelligent and Robotic Systems
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
LADPSO: using fuzzy logic to conduct PSO algorithm
Applied Intelligence
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Hough transform (HT) has been the most common method for circle detection that delivers robustness but adversely demands considerable computational efforts and large memory requirements. As an alternative to HT-based techniques, the problem of shape recognition has also been handled through optimization methods. In particular, extracting multiple circle primitives falls into the category of multi-modal optimization as each circle represents an optimum which must be detected within the feasible solution space. However, since all optimization-based circle detectors focus on finding only a single optimal solution, they need to be applied several times in order to extract all the primitives which results on time-consuming algorithms. This paper presents an algorithm for automatic detection of multiple circular shapes that considers the overall process as a multi-modal optimization problem. In the detection, the approach employs an evolutionary algorithm based on the way in which the animals behave collectively. In such an algorithm, searcher agents emulate a group of animals which interact to each other using simple biological rules. These rules are modeled as evolutionary operators. Such operators are applied to each agent considering that the complete group maintains a memory which stores the optimal solutions seen so-far by applying a competition principle. The detector uses a combination of three non-collinear edge points as parameters to determine circle candidates (possible solutions). A matching function determines if such circle candidates are actually present in the image. Guided by the values of such matching functions, the set of encoded candidate circles are evolved through the evolutionary algorithm so that the best candidate (global optimum) can be fitted into an actual circle within the edge-only image. Subsequently, an analysis of the incorporated memory is executed in order to identify potential local optima which represent other circles. Experimental results over several complex synthetic and natural images have validated the efficiency of the proposed technique regarding accuracy, speed and robustness.