Title:
Anti-Geometric Diffusion for Adaptive Thresholding and Segmentation
Anti-Geometric Diffusion for Adaptive Thresholding and Segmentation
| dc.contributor.author | Manay, Siddharth | |
| dc.contributor.author | Yezzi, Anthony | |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
| dc.date.accessioned | 2013-09-16T19:59:24Z | |
| dc.date.available | 2013-09-16T19:59:24Z | |
| dc.date.issued | 2001-10 | |
| dc.description | © 2001 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
| dc.description | Presented at the 2001 IEEE International Conference on Image Processing (ICIP 2001), 07-10 October 2001, Thessaloniki, Greece. | en_US |
| dc.description | DOI: 101109/ICIP.2001.958622 | en_US |
| dc.description.abstract | In this paper, we present a novel adaptive thresholding technique based upon an anisotropic diffusion model, which may be referred to as the anti-geometric heat flow. In contrast to its more popular counterparts (such as the geometric heat flow) which diffuse parallel to image edges, this model diffuses perpendicular to image edges, yielding surfaces which are naturally suited for adaptive thresholding and segmentation. While it is possible to apply this diffusion for a fixed amount of time to detect features, we discuss how to detect features during the diffusion process, thus avoiding much of the arbitrariness associated with choosing a single scale (and makes the most notorious problem associated with anisotropic diffusion methods, namely “when do you stop?” a moot point). We will demonstrate the perfonnance of this technique on both synthetic and real images, showing applications to thresholding written text and segmentation of mehcal images and scenes. | en_US |
| dc.identifier.citation | Manay, S. & Yezzi, A. (2001). "Anti-Geometric Diffusion for Adaptive Thresholding and Segmentation". Proceedings of the 2001 International Conference on Image Processing (ICIP 2001), Vol.2, October 2001, pp.829-832. | en_US |
| dc.identifier.doi | 10.1109/ICIP.2001.958622 | |
| dc.identifier.isbn | 0-7803-6725-1 | |
| dc.identifier.uri | http://hdl.handle.net/1853/48952 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.publisher.original | Institute of Electrical and Electronics Engineers | |
| dc.subject | Adaptive thresholding | en_US |
| dc.subject | Anisotropic diffusion | en_US |
| dc.subject | Anti-geometric heat flow | en_US |
| dc.subject | Image segmentation | en_US |
| dc.title | Anti-Geometric Diffusion for Adaptive Thresholding and Segmentation | en_US |
| dc.type | Text | |
| dc.type.genre | Proceedings | |
| dspace.entity.type | Publication | |
| local.contributor.author | Yezzi, Anthony | |
| local.contributor.corporatename | School of Electrical and Computer Engineering | |
| local.contributor.corporatename | College of Engineering | |
| relation.isAuthorOfPublication | 53ee63a2-04fd-454f-b094-02a4601962d8 | |
| relation.isOrgUnitOfPublication | 5b7adef2-447c-4270-b9fc-846bd76f80f2 | |
| relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 |
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