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

    Raheja, S and Kumar, A ORCID logoORCID: 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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    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
    Research Centres > Centre for Advanced Computational Science
    Subject terms: Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, Edge detection, Image enhancement, Fuzzy logic, Guided filtering
    URI: https://mmu-uat.leaf.cosector.com/id/eprint/629498
    DOI: https://doi.org/10.1007/s12530-019-09304-6
    ISSN 1868-6486
    e-ISSN 1868-6486

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