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Uni-modal versus joint segmentation for region-based image fusion

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publication9th International Conference on Information Fusion, 2006 (ICIF '06) Florence, Italy
Publisher or commissioning bodyInstitute of Electrical and Electronics Engineers (IEEE)
Pages1 - 8
Number of pages8
ISBN (Print)0972184465, 1424409535
StatePublished - Jul 2006
Event9th International Conference on Information Fusion - Florence, Italy


Conference9th International Conference on Information Fusion
Period1/07/06 → …


A number of segmentation techniques are compared with regard to their usefulness for region-based image and video fusion. In order to achieve this, a new multi-sensor data set is introduced containing a variety of infra-red, visible and pixel fused images together with manually produced "ground truth" segmentations. This enables the objective comparison of joint and unimodal segmentation techniques. A clear advantage to using joint segmentation over unimodal segmentation, when dealing with sets of multi-modal images, is shown. The relevance of these results to region-based image fusion is confirmed with task-based analysis and a quantitative comparison of the fused images produced using the various segmentation algorithms

Additional information

Rose publication type: Conference contribution Sponsorship: This work has been partially funded by the UK MOD Data and Information Fusion Defence Technology Centre. The original “UN Camp”, “Trees”, “Dune” and “Sea” IR and visible images are kindly supplied by TNO Human Factors Research Institute and the Octec images by David Dwyer of Octec Ltd. These images are available online at The “Face” images are taken from the Human Identification at a Distance data set, produced by Equinox Corp. available at Terms of use: Copyright © 2006 IEEE. Reprinted from 9th International Conference on Information Fusion, 2006 (ICIP2006). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

    Research areas

  • multi-modal segmentation, evaluation of segmentation, region-based, image fusion, human segmentation


9th International Conference on Information Fusion

Duration1 Jul 2006 → …

Event: Conference

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