Finite grade pheromone ant colony optimization for image segmentation

• Autorzy: Yuanjing F. , Liangjun K. , Li Y.
• Języki publikacji: EN

Abstrakty

EN

By combining the decision process of ant colony optimization (ACO) with the multistage decision process of image segmentation based on active contour model (ACM), an algorithm called finite grade ACO (FACO) for image segmentation is proposed. This algorithm classifies pheromone into finite grades and updating of the pheromone is achieved by changing the grades and the updated quantity of pheromone is independent from the objective function. The algorithm that provides a new approach to obtain precise contour is proved to converge to the global optimal solutions linearly by means of finite Markov chains. The segmentation experiments with ultrasound heart image show the effectiveness of the algorithm. Comparing the results for segmentation of left ventricle images shows that the ACO for image segmentation is more effective than the GA approach and the new pheromone updating strategy appears good time performance in optimization process.

Słowa kluczowe

EN

active contour model; ant colony optimization; image segmentation

• Wydawca: Stowarzyszenie Elektryków Polskich ; Polska Akademia Nauk ; Wojskowa Akademia Techniczna im. Jarosława Dąbrowskiego
• Czasopismo: Opto-Electronics Review
• Rocznik: 2008
• Tom: Vol. 16, No. 2
• Strony: 163--171
• Opis fizyczny: Bibliogr. 18 poz., il., wykr.

Twórcy

autor

Yuanjing F.

autor

Liangjun K.

autor

Li Y.

• College of Information Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang Province, 310032, China,

Bibliografia

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