Title :
Image segmentation algorithm based on swarm intelligence technology
Author_Institution :
Coll. of Comput. Sci. & Inf. Eng., Harbin Normal Univ., Harbin, China
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;
Conference_Titel :
Intelligent Computing and Internet of Things (ICIT), 2014 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4799-7533-4
DOI :
10.1109/ICAIOT.2015.7111540