DocumentCode :
3386833
Title :
A new method for image segmentation
Author :
Guitang, Wang ; Jianlin, Zhu ; Qingchun, Wei ; Huasheng, Xin ; Peiliang, Cao
Author_Institution :
Inf. Eng. Inst., Guangdong Univ. of Technol., Guangzhou, China
Volume :
2
fYear :
2009
fDate :
28-29 Nov. 2009
Firstpage :
123
Lastpage :
125
Abstract :
On the basis of analyzing the blur images with noise, this paper presents a new segmentation method which is based on the morphology method, fuzzy K-means algorithm and some parts operator of the Canny algorithm. Because of the Canny´s good performance on good detection, good localization and only one response to a single edge, we introduce the course of Canny operator that calculating the value and direction of grads, non-maxima suppression to the grad value and lag threshold process into our post-treatment process. Through experiments, it is demonstrated that the image segmentation method in this paper is very effective.
Keywords :
edge detection; fuzzy set theory; image segmentation; mathematical morphology; mathematical operators; pattern clustering; Canny algorithm operator; blur image analysis; fuzzy K-means algorithm; image noise; image segmentation; lag threshold process; morphology method; nonmaxima suppression; Algorithm design and analysis; Charge coupled devices; Charge-coupled image sensors; Clustering algorithms; Fuzzy control; Image analysis; Image edge detection; Image segmentation; Morphology; Noise figure; Canny operator; edge detection; fuzzy K-means algorithm; mathematical morphology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Industrial Applications, 2009. PACIIA 2009. Asia-Pacific Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4606-3
Type :
conf
DOI :
10.1109/PACIIA.2009.5406610
Filename :
5406610
Link To Document :
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