DocumentCode :
319680
Title :
Image segmentation based on combination of the global and local information
Author :
Qian, Yuntao ; Zhao, Rongchun
Author_Institution :
Dept. of Comput. Sci. & Eng., Northwestern Polytech. Univ., Xian, China
Volume :
1
fYear :
1997
fDate :
26-29 Oct 1997
Firstpage :
204
Abstract :
An image segmentation approach based on modified fuzzy c-mean clustering algorithm is developed. This method deals with the global and local image information at a gross scene level, which incorporates the local information including the edge map and the spatial relationship of the pixels into the parameters of its objective function. But the current clustering based segmentation methods usually incorporate the local information into the feature space, or integrate the global and local information at a local level. In addition, we also propose a fuzzy Gaussian basis function neural network to complete fuzzy clustering on the grey-histogram of image as the initial solution, which can automatically determine the number of clusters, and is strong and robust
Keywords :
Gaussian processes; edge detection; fuzzy neural nets; image recognition; image segmentation; clustering based segmentation methods; edge detection; edge map; feature space; fuzzy Gaussian basis function neural network; global image information; grey-histogram; gross scene level; image segmentation; local image information; objective function parameters; spatial pixels relationship; Clustering algorithms; Computer science; Ellipsoids; Fuzzy neural networks; Histograms; Image edge detection; Image segmentation; Layout; Neural networks; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1997. Proceedings., International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8183-7
Type :
conf
DOI :
10.1109/ICIP.1997.647447
Filename :
647447
Link To Document :
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