Edge detection based on type-1 fuzzy logic and guided smoothening

Raheja, S and Kumar, A ORCID: https://orcid.org/0000-0003-4263-7168 (2021) Edge detection based on type-1 fuzzy logic and guided smoothening. Evolving Systems, 12 (2). pp. 447-462. ISSN 1868-6486

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Official URL: https://link.springer.com/article/10.1007/s12530-0...

Abstract

Edge detection is an important phenomenon in computer vision. Edge detection is helpful in contour detection and thus helpful in obtaining the important information. Edge detection process heavily depends on chosen technique. Soft computing techniques are considered as powerful edge detection methods due to their adaptability. This paper presents a fuzzy logic based edge detection method where the quality of edges is controlled using sharpening guided filter and noise due to the sharpening is controlled using Gaussian filter. The accuracy of the method is judged using a variety of statistical measures. It has been found that by proper selecting the smoothening parameters a significant improvement in the detected edges can be obtained.

Item Type:	Article
Peer-reviewed:	Yes
Date Deposited:	25 Apr 2022 08:11
Publisher:	Springer Verlag
Additional Information:	This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s12530-019-09304-6
Divisions:	Faculties > Science and Engineering
Subject terms:	Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, Edge detection, Image enhancement, Fuzzy logic, Guided filtering
URI:	https://e-space.mmu.ac.uk/id/eprint/629498
DOI:	https://doi.org/10.1007/s12530-019-09304-6
ISSN	1868-6486
e-ISSN	1868-6486

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