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

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

  • Sidra Naeem
  • Sajid Siraj
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
Number of pages6
ISBN (Print)978076955548
Publication statusPublished - 2013
Event2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013) - Manchester, United Kingdom
Duration: 13 Oct 201316 Oct 2013


Conference2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013)
CountryUnited Kingdom


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ID: 673964