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Proceedings Paper

Image thresholding using minimal fuzzy entropy based on 2D gray histogram
Author(s): Zhengguang Liu; Xiuge Che; Juntao Xue; Guixiong G. Shen
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Paper Abstract

A new method of minimal fuzzy entropy segmentation is introduced. It adopts a new membership function for the consistency and concentricity in the object and its background. A new 2D fuzzy entropy thresholding method is also developed, which is based on 2D gray historgram. The gray values of every pixel and its neighboring region are used in this 2D method. The experimental results show that the minimal fuzzy entropy method is very useful in the segmentation of some images and the 2D method has a good performance of resisting noise and good robustness. The segmentatiaon of using 2D is much better than 1D for most images, and the new method can be easily extended to other 1D entropy imaging thresholding.

Paper Details

Date Published: 25 September 2003
PDF: 6 pages
Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.539063
Show Author Affiliations
Zhengguang Liu, Tianjin Univ. (China)
Xiuge Che, Nankai Univ. (China)
Juntao Xue, Tianjin Univ. (China)
Guixiong G. Shen, Univ. of Hong Kong (China)


Published in SPIE Proceedings Vol. 5286:
Third International Symposium on Multispectral Image Processing and Pattern Recognition
Hanqing Lu; Tianxu Zhang, Editor(s)

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