DocumentCode
327931
Title
Thresholding based on fuzzy partition of 2D histogram
Author
Cheng, H.D. ; Chen, Y.H.
Author_Institution
Dept. of Comput. Sci., Utah State Univ., Logan, UT, USA
Volume
2
fYear
1998
fDate
16-20 Aug 1998
Firstpage
1616
Abstract
Thresholding is an important topic of image processing. This paper proposes a thresholding approach by performing a fuzzy partition on a 2D histogram of the image. The 2D fuzzy partition method and membership assignment are based on fuzzy relation of two fuzzy sets, which is characterized by a set of parameters (a, b, c). The proposed approach has been tested on various images, and the results have demonstrated that the proposed 2D fuzzy approach outperforms the 2D nonfuzzy approach and the 1D fuzzy approach
Keywords
fuzzy set theory; image processing; maximum entropy methods; pattern recognition; 2D histogram; fuzzy entropy; fuzzy partition; fuzzy set theory; image processing; membership assignment; thresholding; Brightness; Computer science; Entropy; Fuzzy sets; Fuzzy systems; Histograms; Image processing; Pattern recognition; Pixel; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
Conference_Location
Brisbane, Qld.
ISSN
1051-4651
Print_ISBN
0-8186-8512-3
Type
conf
DOI
10.1109/ICPR.1998.712025
Filename
712025
Link To Document