Fuzzy Approach for Enhanced Edge Detection Algorithm by Entropy Optimization

1
Dr. Gurpreet Kaur
Dr. Gurpreet Kaur
2
Varun Raj
Varun Raj
1 Guru Gobind Singh Indraprasth University, New Delhi, India.

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GJRE Volume 12 Issue J2

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The objective of our study was to evaluate, in a population of Togolese People Living With HIV(PLWHIV), the agreement between three scores derived from the general population namely the Framingham score, the Systematic Coronary Risk Evaluation (SCORE), the evaluation of the cardiovascular risk (CVR) according to the World Health Organization.
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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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No external funding was declared for this work.

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The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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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): .

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Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

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v1.2

Issue date

May 8, 2012

Language

English

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Fuzzy Approach for Enhanced Edge Detection Algorithm by Entropy Optimization

Dr. Gurpreet Kaur
Dr. Gurpreet Kaur Guru Gobind Singh Indraprasth University, New Delhi, India.
Varun Raj
Varun Raj

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