A modified fuzzy ART for image segmentation

L. Cinque, G. Foresti, A. Gumina, S. Levialdi
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引用次数: 9

Abstract

This paper presents a clustering approach for image segmentation based on a modified fuzzy ART model. The goal of the proposed approach is to find a simple model able to instance a prototype for each cluster in order to avoid complex post-processing phases. Some results and comparisons with other models present in the literature, like SOM and original fuzzy ART are presented. Qualitative and quantitative evaluations confirm the validity of our approach.
一种用于图像分割的改进模糊ART
提出了一种基于改进模糊ART模型的聚类图像分割方法。该方法的目标是找到一个简单的模型,能够为每个集群实例化一个原型,以避免复杂的后处理阶段。给出了一些结果,并与文献中的其他模型(如SOM和原始模糊ART)进行了比较。定性和定量评估证实了我们方法的有效性。
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