Ant Colony Optimization for Phase Change Image Sequences Segementation

Author

Feng, Yuanjing ; Feng, Zuren ; Li Yu

Author_Institution

Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou

Volume

1

fYear

0

fDate

0-0 0

Firstpage

4274

Lastpage

4278

Abstract

Ant colony optimization (ACO) based phase change image sequences segmentation algorithm is presented. In the algorithm, phase change image sequences are changed into multiple associated sub-image by region division which includes the moving information of the moving contour. An ACO for image segmentation based on active contour model is proposed for sub-image segmentation, which converts image segmentation to a problem of searching for the best path in a constrained region. The segmentation results of sub-images are converted into the phase change contour. The experiment results show that the algorithm extracts the phase change active contour well

Keywords

artificial life; image segmentation; image sequences; optimisation; search problems; active contour model; ant colony optimization; phase change contour; phase change image sequences segmentation; Active contours; Ant colony optimization; Automation; Educational institutions; Image converters; Image segmentation; Image sequences; Intelligent control; Laboratories; Systems engineering and theory; active contour model; ant colony optimization; image segmentation; phase change image sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713181

Filename

1713181