A framework to select edge detection method using multi-criteria decision making
Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed)
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 language | English |
|---|---|
| Title of host publication | 2013 IEEE international conference on Systems, man, and cybernetics |
| Subtitle of host publication | SMC 2013 |
| Place of Publication | Picataway |
| Publisher | IEEE |
| Pages | 730-735 |
| Number of pages | 6 |
| ISBN (Print) | 978076955548 |
| DOIs | |
| Publication status | Published - 2013 |
| Event | 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013) - Manchester, United Kingdom Duration: 13 Oct 2013 → 16 Oct 2013 |
Conference
| Conference | 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013) |
|---|---|
| Country | United Kingdom |
| City | Manchester |
| Period | 13/10/13 → 16/10/13 |
Documents
- SIRAJ_2013_cright_IEEE_A Framework to Select Edge Detection Method Using Multi-criteria Decision Making
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Submitted manuscript, 9.89 MB, PDF document
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