Assessment of the contribution of sustainability indicators to sustainable development: a novel approach using fuzzy set theory

2001 ◽  
Vol 86 (2) ◽  
pp. 173-185 ◽  
Author(s):  
A.M.G Cornelissen ◽  
J van den Berg ◽  
W.J Koops ◽  
M Grossman ◽  
H.M.J Udo
Keyword(s):  
Sustainable Development ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Sustainability Indicators ◽  
Novel Approach

Novel Approach to Pavement Cracking Detection Based on Fuzzy Set Theory

1999 ◽  
Vol 13 (4) ◽  
pp. 270-280 ◽  
Author(s):  
H. D. Cheng ◽  
Jim-Rong Chen ◽  
Chris Glazier ◽  
Y. G. Hu
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Novel Approach

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.

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