DocumentCode :
3391736
Title :
Binary fuzzy rough set model based on triangle modulus and its application to image processing
Author :
Wang Dan ; Wu, Meng-Da
Author_Institution :
Dept. of Mathematic & Syst. Sci., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2009
fDate :
15-17 June 2009
Firstpage :
249
Lastpage :
255
Abstract :
Rough sets theory is an important tool that process uncertainty information. In this paper, image processing based on rough sets theory is discussed in detail. The paper presents a binary fuzzy rough set model based on triangle modulus, which describes binary relationship by upper approximation and lower approximation. As image can be described by binary relationship, the upper approximation and lower approximation can be used to represent an image. The model in this paper is well fit for processing image that have gentle gray change. An edge detection algorithm by the upper approximation and the lower approximation of image is presented, and image denoising also is discussed. At last, its better effect can be testified by many experiments.
Keywords :
approximation theory; edge detection; fuzzy set theory; image denoising; image representation; rough set theory; approximation theory; binary fuzzy rough set model; edge detection algorithm; gray image; image denoising; image processing; image representation; triangle modulus; Approximation algorithms; Change detection algorithms; Fuzzy set theory; Fuzzy sets; Image denoising; Image edge detection; Image processing; Pattern analysis; Rough sets; Uncertainty; Rough Sets; edge detection; image denoising; the upper (lower) approximation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Informatics, 2009. ICCI '09. 8th IEEE International Conference on
Conference_Location :
Kowloon, Hong Kong
Print_ISBN :
978-1-4244-4642-1
Type :
conf
DOI :
10.1109/COGINF.2009.5250738
Filename :
5250738
Link To Document :
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