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 :
بازگشت