DocumentCode :
416704
Title :
Image segmentation using multiple and partially evolved Hopfield neural networks
Author :
Ming, Li ; Xiaoqin, Yang ; Linxia, Zhou
Author_Institution :
Dept. of Test & Control Eng., Nanchang Inst. of Aeronaut. Technol., China
Volume :
3
fYear :
2003
fDate :
4-6 Aug. 2003
Firstpage :
2510
Abstract :
This paper proposed an image segmentation method with multiple and partially evolved Hopfield neural networks. These neural networks, which are used to generate the threshold surface by interpolating the gray levels of the edge points into a segmentation threshold surface, are partially evolved to escape from possible local optima state.
Keywords :
Hopfield neural nets; genetic algorithms; image segmentation; Hopfield neural networks; genetic algorithm; gray levels; image segmentation; local optima state; segmentation threshold surface; threshold surface;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE 2003 Annual Conference
Conference_Location :
Fukui, Japan
Print_ISBN :
0-7803-8352-4
Type :
conf
Filename :
1323641
Link To Document :
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