Title:
A Real-Time Curve Evolution-Based Image Fusion Algorithm for Multisensory Image Segmentation
A Real-Time Curve Evolution-Based Image Fusion Algorithm for Multisensory Image Segmentation
dc.contributor.author | Ding, Yuhua | |
dc.contributor.author | Vuchtsevunos, George J. | |
dc.contributor.author | Yezzi, Anthony | |
dc.contributor.author | Daley, Wayne | |
dc.contributor.author | Ferri, Bonnie H. | |
dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
dc.date.accessioned | 2013-12-03T17:49:23Z | |
dc.date.available | 2013-12-03T17:49:23Z | |
dc.date.issued | 2003-04 | |
dc.description | © 2003 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 | This paper was originally published in the Proceedings of the 2003 IEEE lntemational Conference on Acoustics, Speech, & Signal Processing, April 6-10, 2003, Hong Kong (cancelled). Reprinted with permission. | |
dc.description | DOI: 10.1109/ICME.2003.1220931 | |
dc.description.abstract | A partial differential equation (PDE)-based feature-level image fusion approach is proposed for multisensory image segmentation. The energy functional of the proposed fusion model is a weighted sum of several functionals, each constructed based on the characteristics of the sensor image. The weight selection decides the way that the model handles redundant, conflicting, or complementary information involved in the multisensory data. The method is implemented using level sets and is fast enough for real-time segmentation tasks. Finally the algorithm is applied to the segmentation of x-ray and visual images, and the results show that the fusion algorithm is efficient, accurate, and robust. | en_US |
dc.embargo.terms | null | en_US |
dc.identifier.citation | Ding, Y.; Vachtsevanos, G.J.; Yezzi, A.J.; Daley, W.; & Heck-Ferri, B.S. (2003). “A Real-Time Curve Evolution-Based Image Fusion Algorithm for Multisensory Image Segmentation”. Proceedings of the 2003 International Conference on Multimedia and Expo (ICME '03), Vol. 1, July 2003, pp.I,369-72. | en_US |
dc.identifier.doi | 10.1109/ICME.2003.1220931 | |
dc.identifier.isbn | 0-7803-7965-9 (ICME 2003) | |
dc.identifier.uri | http://hdl.handle.net/1853/49753 | |
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 | Fusion | en_US |
dc.subject | Level sets | en_US |
dc.subject | Multisensory image segmentation | en_US |
dc.subject | Partial differential equation | en_US |
dc.subject | Sensor image | en_US |
dc.subject | Visual image | en_US |
dc.subject | X-ray image | en_US |
dc.title | A Real-Time Curve Evolution-Based Image Fusion Algorithm for Multisensory Image Segmentation | en_US |
dc.type | Text | |
dc.type.genre | Proceedings | |
dspace.entity.type | Publication | |
local.contributor.author | Yezzi, Anthony | |
local.contributor.author | Ferri, Bonnie H. | |
local.contributor.corporatename | School of Electrical and Computer Engineering | |
local.contributor.corporatename | College of Engineering | |
relation.isAuthorOfPublication | 53ee63a2-04fd-454f-b094-02a4601962d8 | |
relation.isAuthorOfPublication | e8b8974b-0988-4c56-ae82-fbf253466591 | |
relation.isOrgUnitOfPublication | 5b7adef2-447c-4270-b9fc-846bd76f80f2 | |
relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 |
Files
Original bundle
1 - 1 of 1
- Name:
- icme_RealTime_Curve_Evolution.pdf
- Size:
- 323.87 KB
- Format:
- Adobe Portable Document Format
- Description:
License bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- license.txt
- Size:
- 3.13 KB
- Format:
- Item-specific license agreed upon to submission
- Description: