Machine vision
Swarm intelligence
Particle Swarn Optimization with Fast Local Search for the Blind Traveling Salesman Problem
HIS '05 Proceedings of the Fifth International Conference on Hybrid Intelligent Systems
Particle Swarm Optimization for the Multidimensional Knapsack Problem
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
An object detection and recognition system for weld bead extraction from digital radiographs
Computer Vision and Image Understanding
Self-adapting evolutionary parameters: encoding aspects for combinatorial optimization problems
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Object detection for computer vision using a robust genetic algorithm
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
An approach to multimodal biomedical image registration utilizing particle swarm optimization
IEEE Transactions on Evolutionary Computation
A Compact Genetic Algorithm with Elitism and Mutation Applied to Image Recognition
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Markerless human articulated tracking using hierarchical particle swarm optimisation
Image and Vision Computing
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Particle Swarm Optimization (PSO) is an evolutionary computation technique frequently used for optimization tasks. This work aims at applying PSO for recognizing specific patterns in complex images. Experiments were done with gray level and color images, with and without noise. PSO was able to find predefined reference images, submitted to translation, rotation, scaling, occlusion, noise and change in the viewpoint in the landscape image. Several experiments were done to evaluate the performance of PSO. Results show that the proposed method is robust and very promising for real-world applications.