DocumentCode :
456478
Title :
Active Contour Optimization using Particle Swarm Optimizer
Author :
Asl, Mahdi Ahmadi ; Seyedin, Seyed Alireza
Author_Institution :
Dept. of Electr. Eng., Ferdowsi Univ. of Mashhad, Mashad
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
1522
Lastpage :
1523
Abstract :
Summary form only given. Active models are curves or surfaces defined within an image domain that can move under the influence of internal forces, which are defined within the curve or surface itself, and external forces, which are computed from the image data. The internal forces are designed to keep the model smooth during deformation. The external forces are defined to move the model toward an object boundary or other desired features within an image. By constraining extracted boundaries to be smooth and incorporating other prior information about the object shape, deformable models offer robustness to both image noise and boundary gaps and allow integrating boundary elements into a coherent and consistent mathematical description. Such a boundary description can then be readily used by subsequent applications. Considering all the experimental results, finally we concluded that if time is an important factor for a special problem, PSO would be the better choice and if it is not the case, both of the algorithms namely GA and PSO, qualify for snake deforming through energy functional minimizing
Keywords :
computational geometry; genetic algorithms; image processing; particle swarm optimisation; active contour optimization; active deformable model; boundary gap element; energy functional minimization; genetic algorithm; image curve; image data; image deformation; image feature; image noise; image surface; object shape boundary; particle swarm optimizer; Active contours; Data mining; Deformable models; Evolutionary computation; Finite element methods; Genetic algorithms; Optical computing; Partial differential equations; Particle swarm optimization; Solid modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technologies, 2006. ICTTA '06. 2nd
Conference_Location :
Damascus
Print_ISBN :
0-7803-9521-2
Type :
conf
DOI :
10.1109/ICTTA.2006.1684608
Filename :
1684608
Link To Document :
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