Fuzzy-set-based hierarchical networks for information fusion in computer vision

1992 ◽  
Vol 5 (2) ◽  
pp. 335-350 ◽  
Author(s):  
Raghu Krishnapuram ◽  
Joonwhoan Lee
Keyword(s):  
Computer Vision ◽  
Information Fusion ◽  
Fuzzy Set ◽  
Hierarchical Networks

A NOVEL APPROACH TO IMAGE THRESHOLDING BASED ON 2D HOMOGENEITY HISTOGRAM AND MAXIMUM FUZZY ENTROPY

2011 ◽  
Vol 07 (01) ◽  
pp. 105-133 ◽  
Author(s):  
H. D. CHENG ◽  
YANHUI GUO ◽  
YINGTAO ZHANG
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Fuzzy Entropy ◽  
Image Thresholding ◽  
Novel Approach ◽  
Entropy Principle

Image thresholding is an important topic for image processing, pattern recognition and computer vision. Fuzzy set theory has been successfully applied to many areas, and it is generally believed that image processing bears some fuzziness in nature. In this paper, we employ the newly proposed 2D homogeneity histogram (homogram) and the maximum fuzzy entropy principle to perform thresholding. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively. Especially, it not only can process "clean" images, but also can process images with different kinds of noises and images with multiple kinds of noise well without knowing the type of the noise, which is the most difficult task for image thresholding. It will be useful for applications in computer vision and image processing.

Fuzzy set information fusion in land mine detection

1999 ◽  
Author(s):  
Bruce N. Nelson ◽  
Paul D. Gader ◽  
James M. Keller
Keyword(s):  
Information Fusion ◽  
Fuzzy Set ◽  
Mine Detection ◽  
Land Mine ◽  
Land Mine Detection

Application of Uncertain Information Fusion in Diagnosis Decision of Electronic Equipment

2013 ◽  
Vol 341-342 ◽  
pp. 715-718
Author(s):  
Jin Luo ◽  
Qi Bin Deng
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Fuzzy Set ◽  
Fuzzy Theory ◽  
Electronic Equipment ◽  
Uncertain Information ◽  
Combination Rule ◽  
Fault Features ◽  
Diagnosis Method ◽  
Fuzzy Target

Focuses on how to dispose the multi-source uncertain information and promote the testability evaluation and fault diagnosis capability of the electronic equipment, this paper uses fuzzy theory in the uncertain information description and modeling. Based on the fuzzy set description of fuzzy target, new method is proposed to obtain fuzzy evidences from fuzzy fault features, and then, Dempster-Shafer combination rule are used to fuse multi-source fuzzy evidence to get diagnosis results. The proposed method of fuzzy evidence extraction can reduces uncertainties in fusion makings and improves fault identifications, and the fusion diagnosis method based on multi fuzzy evidence matching enhances the precision and reliability of the system fault diagnosis decision furthermore.

An Information Fusion Framework of Traffic Counts Forecasts Based on Concepts from Fuzzy Set Theory.

2009 ◽  
Vol 42 (15) ◽  
pp. 278-285
Author(s):  
Antony Stathopoulos ◽  
Matthew G. Karlaftis ◽  
Loukas Dimitriou
Keyword(s):  
Set Theory ◽  
Information Fusion ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Traffic Counts ◽  
Fusion Framework
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