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

JJ Lewis, SG Nikolov, CN Canagarajah, DR Bull, A Toet

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

20 Citations (Scopus)
363 Downloads (Pure)

Abstract

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
Translated title of the contributionUni-modal versus joint segmentation for region-based image fusion
Original languageEnglish
Title of host publication9th International Conference on Information Fusion, 2006 (ICIF '06) Florence, Italy
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1 - 8
Number of pages8
ISBN (Print)0972184465, 1424409535
DOIs
Publication statusPublished - Jul 2006
Event9th International Conference on Information Fusion - Florence, Italy
Duration: 1 Jul 2006 → …

Conference

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

Bibliographical note

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 ImageFusion.org. The “Face”
images are taken from the Human Identification at a
Distance data set, produced by Equinox Corp. available
at equinoxsensors.com.

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Keywords

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

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  • Cite this

    Lewis, JJ., Nikolov, SG., Canagarajah, CN., Bull, DR., & Toet, A. (2006). Uni-modal versus joint segmentation for region-based image fusion. In 9th International Conference on Information Fusion, 2006 (ICIF '06) Florence, Italy (pp. 1 - 8). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICIF.2006.301565