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
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