A framework to select edge detection method using multi-criteria decision making

Sidra Naeem, Sajid Siraj

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

    328 Downloads (Pure)

    Abstract

    In the fields of computer vision and image processing, edge detection refers to the identification and localization of significant changes in a digital image. This article presents a survey of widely-used edge detection techniques including linear approaches, morpohlogical operations, multi-resolution analysis, and machine learning methods. Since there exists no single method that is applicable in all situations, different methods are deployed for different applications. A hierarchical framework based on multiple criteria has been proposed here that can facilitate the process of selecting the most appropriate edge detection method in a given scenario. Use of the proposed framework has been explained through an example of medical images. Finally, possible areas for further exploration have been highlighted. collapse
    Original languageEnglish
    Title of host publication2013 IEEE international conference on Systems, man, and cybernetics
    Subtitle of host publicationSMC 2013
    Place of PublicationPicataway
    PublisherIEEE
    Pages730-735
    Number of pages6
    ISBN (Print)978076955548
    DOIs
    Publication statusPublished - 2013
    Event2013 IEEE International Conference on Systems, Man and Cybernetics - Manchester, United Kingdom
    Duration: 13 Oct 201316 Oct 2013

    Conference

    Conference2013 IEEE International Conference on Systems, Man and Cybernetics
    Abbreviated titleSMC 2013
    Country/TerritoryUnited Kingdom
    CityManchester
    Period13/10/1316/10/13

    Keywords

    • Edge detection,
    • boundary,
    • filters

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