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A New Image Thresholding Algorithm Based on Fuzzy sets Theory

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5 Author(s)
Zhaoyu Pian ; Northeastern Univ., Shenyang ; Liqun Gao ; Kun Wang ; Li Guo
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Many classical measures partition image according to a single property. Moreover, many schemes suffer from the lack of evaluation of image quality at the global level. This paper proposes a novel two phases image thresholding measure that uses both global and local image properties for grayscale images. In the local phase, we present a novel thresholding technology which proposes threshold as multi-properties (ultra-fuzzy entropy and ultra-fuzzy similarity) based on type II fuzzy (ultra-fuzzy) sets. In the global phase, a nonlinear contrast intensification function is used to further enhance the image. In experiments conducted on various classic images, this algorithm showed notable visual improvement in comparison with common measures.

Published in:

Control and Automation, 2007. ICCA 2007. IEEE International Conference on

Date of Conference:

May 30 2007-June 1 2007