DocumentCode
2446220
Title
Image thresholding via possibilistic clustering
Author
Medasani, Swarup ; Krishnapuram, Raghu
Author_Institution
Dept. of Electr. & Comput. Eng., Missouri Univ., Columbia, MO, USA
fYear
1994
fDate
18-21 Dec 1994
Firstpage
423
Lastpage
426
Abstract
In this paper, we introduce a new technique for gray-level thresholding based on the Possibilistic C-Means (PCM) algorithm. The PCM-based thresholding is compared with two other traditional thresholding techniques due to Otsu (1979) and Kullback (1959), and also with a technique based on the Fuzzy C-Means algorithm
Keywords
image processing; possibility theory; PCM-based thresholding; Possibilistic C-Means; gray-level thresholding; image thresholding; possibilistic clustering; thresholding techniques; Clustering algorithms; Clustering methods; Computer vision; Gray-scale; Histograms; Image analysis; Image converters; Partitioning algorithms; Phase change materials; Pixel;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society Biannual Conference, 1994. Industrial Fuzzy Control and Intelligent Systems Conference, and the NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic,
Conference_Location
San Antonio, TX
Print_ISBN
0-7803-2125-1
Type
conf
DOI
10.1109/IJCF.1994.375074
Filename
375074
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