THRESHOLD SELECTION BASED ON FUZZY C-PARTITION ENTROPY APPROACH

Citation
Hd. Cheng et al., THRESHOLD SELECTION BASED ON FUZZY C-PARTITION ENTROPY APPROACH, Pattern recognition, 31(7), 1998, pp. 857-870
Citations number
23
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Computer Science Artificial Intelligence","Engineering, Eletrical & Electronic","Computer Science Artificial Intelligence
Journal title
ISSN journal
0031-3203
Volume
31
Issue
7
Year of publication
1998
Pages
857 - 870
Database
ISI
SICI code
0031-3203(1998)31:7<857:TSBOFC>2.0.ZU;2-N
Abstract
Thresholding is an important topic for image processing, pattern recog nition and computer vision. Selecting thresholds is a critical issue f or many applications. The fuzzy set theory has been successfully appli ed to many areas, such as control, image processing, pattern recogniti on, computer vision, medicine, social science, etc. It is generally be lieved that image processing bears some fuzziness in nature. In this p aper, we use the concept of fuzzy c-partition and the maximum fuzzy en tropy principle to select threshold values for gray-level images. We h ave conducted experiments on many images. The experimental results dem onstrate that the proposed approach can select the thresholds automati cally and effectively, and the resulting images can preserve the main features of the components of the original images very well. (C) 1998 Pattern Recognition Society. Published by Elsevier Science Ltd. All ri ghts reserved.