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AN IMAGE SEGMENTATION APPROACH BASED ON FUZZY-NEURAL-NETWORK HYBRID SYSTEM

AN IMAGE SEGMENTATION APPROACH BASED ON FUZZY-NEURAL-NETWORK HYBRID SYSTEM
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摘要 This paper presents a new solution to the image segmentation problem, which is based on fuzzy-neural-network hybrid system (FNNHS). This approach can use the experiential knowledge and the ability of neural networks which learn knowledge from the examples, to obtain the well performed fuzzy rules. Furthermore this fuzzy inference system is completed by neural network structure which can work in parallel. The segmentation process consists of pre-segmentation based on region growing algorithm and region merging based on FNNHS. The experimental results on the complicated image manifest the utility of this method. This paper presents a new solution to the image segmentation problem, which is based on fuzzy-neural-network hybrid system (FNNHS). This approach can use the experiential knowledge and the ability of neural networks which learn knowledge from the examples, to obtain the well performed fuzzy rules. Furthermore this fuzzy inference system is completed by neural network structure which can work in parallel. The segmentation process consists of pre-segmentation based on region growing algorithm and region merging based on FNNHS. The experimental results on the complicated image manifest the utility of this method.
出处 《Journal of Electronics(China)》 1997年第4期352-356,共5页 电子科学学刊(英文版)
基金 National Nature Science Foundation of China
关键词 COMPUTER VISION Image segmentation Fuzzy LOGIC NEURAL NETWORK Computer vision Image segmentation Fuzzy logic Neural network
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