DocumentCode
2705383
Title
Image segmentation algorithm based on swarm intelligence technology
Author
Hui-jie Sun
Author_Institution
Coll. of Comput. Sci. & Inf. Eng., Harbin Normal Univ., Harbin, China
fYear
2015
fDate
17-18 Jan. 2015
Firstpage
68
Lastpage
71
Abstract
Image segmentation is one of the key technologies in image processing, image segmentation quality relates to subsequent processing directly such as image measurement and image recognition, etc. This paper presents a new intelligent optimization algorithm: (artificial fish swarm algorithm, artificial bacterial swarm algorithm and artificial bee colony swarm algorithm), a new method of image segmentation, namely the wavelet transform for segmented images, combined with gray-scale morphology and rough sets theory to solve the problem of image noise, uses a new intelligent optimization algorithm to improve the effect of segmentation, the segmentation performance better, faster, and has important theoretical significance and practical value.
Keywords
ant colony optimisation; image segmentation; rough set theory; swarm intelligence; wavelet transforms; artificial bacterial swarm algorithm; artificial bee colony swarm algorithm; artificial fish swarm algorithm; gray-scale morphology; image measurement; image noise; image processing; image recognition; image segmentation algorithm; image segmentation quality; intelligent optimization algorithm; rough sets theory; swarm intelligence technology; wavelet transform; Classification algorithms; Image recognition; Image segmentation; Manganese; Optimization; Sun; artificial fish swarm algorithm; image segmentation; rough sets; swarm intelligence;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computing and Internet of Things (ICIT), 2014 International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4799-7533-4
Type
conf
DOI
10.1109/ICAIOT.2015.7111540
Filename
7111540
Link To Document