基于模糊--神经网络混合系统的图象分割方法
AN IMAGE SEGMENTATION APPROACH BASED ON FUZZY-NEURAL-NETWORK HYBRID SYSTEM
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摘要: 本文提出了一种基于模糊-神经网络混合系统(FNNHS)的图象分割方法。它可以利用人的经验知识和神经网络从样本数据中学习知识的能力,得到性能良好的模糊规则,并且可以通过神经网络结构实现模糊推理。分割过程由基于区域生长的预分割和基于FNNHS的区域合并两步构成。实验表明,该方法用于复杂图象分割具有很好的效果。Abstract: This paper presents an image segmentation approach which is based on fuzzy-neural-network hybrid system(FNNHS). This approach can use the empirical 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. The segmentation process consists of pre-segmentation based on region growing algorithm and region merging based on FNNHS. The experiments illustrate the power and efficiency of this method used for complicated image.
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