模糊划分熵的新定义及其在图像分割中的应用
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TP391.41

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A NEW DEFINITION OF FUZZY PARTITION ENTROPY AND ITS APPLICATION TO IMAGE SEGMENTATION
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    摘要:

    介绍了模糊划分的原理,提出用条件概率与条件熵定义模糊划分的熵,并基于最大熵原理设计了一种新的灰度直方图阈值选取算法。比较可见KSW熵法是本文方法的一个特例,本文方法是KSW熵法在模糊集上的推广,对几例真实目标图像的对比分割实验结果表明本文方法性能优越。

    Abstract:

    Based upon the maximum fuzzy partition entropy principle, a novel approach for image segmentation was presented. After the concept of fuzzy partition was introduced briefly, a new definition of fuzzy partition entropy was proposed. A threshold selection approach from gray level histogram through maximizing the entropy of fuzzy partition was put forward. It was demonstrated that KSW entropic thresholding method is just a special case of the approach proposed herein. The experiment was conducted on three real object images. The results show that the proposed approach has better performances than some classical threshold selection methods do.

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金立左 夏良正.模糊划分熵的新定义及其在图像分割中的应用[J].红外与毫米波学报,2000,19(3):219~223]. JIN Li-Zuo, XIA Liang-Zheng. A NEW DEFINITION OF FUZZY PARTITION ENTROPY AND ITS APPLICATION TO IMAGE SEGMENTATION[J]. J. Infrared Millim. Waves,2000,19(3):219~223.]

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