DocumentCode
584472
Title
Image Segmentation Using Thresholding and Artificial Fish-Swarm Algorithm
Author
Zhiwei, Ye ; Qinyun, Li ; Mengdi, Zeng ; Wei, Liu
Author_Institution
Sch. of Comput. Sci., Hubei Univ. of Technol., Wuhan, China
fYear
2012
fDate
11-13 Aug. 2012
Firstpage
1529
Lastpage
1532
Abstract
Image segmentation is an important technology for image processing. Many segmentation methods have been brought forward for image segmentation, among these methods thresholding is the simplest and effective method in image segmentation. In general, the thresholding method based on two-dimensional histogram can provide better results than that of one-dimension histogram. However, for more accurate thresholding, much more time has to pay. Thus, this paper proposes a novel approach to two-dimensional threshold selection based on artificial fish-swarm algorithm and two-dimensional Fisher function criterion. In final, experiments results demonstrate that the proposed method performs well which is a good method to help select optimum 2D thresholds.
Keywords
image segmentation; optimisation; artificial fish-swarm algorithm; image processing; image segmentation; optimum 2D threshold selection; two-dimensional Fisher function criterion; two-dimensional histogram; Algorithm design and analysis; Computer science; Educational institutions; Histograms; Image segmentation; Marine animals; Signal processing algorithms; 2-D Fisher Function; Artificial fish-swarm algorithm; image segmentation; thresholding;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4673-0721-5
Type
conf
DOI
10.1109/CSSS.2012.383
Filename
6394622
Link To Document