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ReserarchID
AQC59
In this paper fuzzy based canny edge detection is explained. Global contrast intensification and local fuzzy edge detection are the two phases explained and is then merged with Canny operator for better results specially for noisy images and low contrast images. The resultant images are obtained using MATLAB which is the most convenient software and is efficient in terms of Image Processing as it is one of its toolbox. Although first-order linear filters constitute the algorithms most widely applied to edge detection in digital images but they don’t allow good results to be obtained where the contrast varies a lot, due to non-uniform lighting, as it happens during acquisition of most part of natural images.
Dr. Gurpreet Kaur. 2012. \u201cFuzzy Approach for Enhanced Edge Detection Algorithm by Entropy Optimization\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 12 (GJRE Volume 12 Issue J2): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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Total Score: 107
Country: India
Subject: Global Journal of Research in Engineering - J: General Engineering
Authors: Dr. Gurpreet Kaur, Varun Raj (PhD/Dr. count: 1)
View Count (all-time): 229
Total Views (Real + Logic): 5338
Total Downloads (simulated): 2634
Publish Date: 2012 05, Tue
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In this paper fuzzy based canny edge detection is explained. Global contrast intensification and local fuzzy edge detection are the two phases explained and is then merged with Canny operator for better results specially for noisy images and low contrast images. The resultant images are obtained using MATLAB which is the most convenient software and is efficient in terms of Image Processing as it is one of its toolbox. Although first-order linear filters constitute the algorithms most widely applied to edge detection in digital images but they don’t allow good results to be obtained where the contrast varies a lot, due to non-uniform lighting, as it happens during acquisition of most part of natural images.
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