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Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Editor: Stephen A. Burns
  • Vol. 23, Iss. 10 — Oct. 1, 2006
  • pp: 2462–2470

Object-of-interest image segmentation based on human attention and semantic region clustering

Byoung Chul Ko and Jae-Yeal Nam  »View Author Affiliations


JOSA A, Vol. 23, Issue 10, pp. 2462-2470 (2006)
http://dx.doi.org/10.1364/JOSAA.23.002462


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Abstract

We propose a novel object-of-interest (OOI) segmentation algorithm for various images that is based on human attention and semantic region clustering. As object-based image segmentation is beyond current computer vision techniques, the proposed method segments an image into regions, which are then merged as a semantic object. At the same time, an attention window (AW) is created based on the saliency map and saliency points from an image. Within the AW, a support vector machine is used to select the salient regions, which are then clustered into the OOI using the proposed region merging. Unlike other algorithms, the proposed method allows multiple OOIs to be segmented according to the saliency map.

© 2006 Optical Society of America

OCIS Codes
(100.2960) Image processing : Image analysis
(100.5010) Image processing : Pattern recognition
(110.2960) Imaging systems : Image analysis
(330.1800) Vision, color, and visual optics : Vision - contrast sensitivity
(330.1880) Vision, color, and visual optics : Detection

ToC Category:
Image Processing

History
Original Manuscript: January 6, 2006
Revised Manuscript: March 22, 2006
Manuscript Accepted: April 26, 2006

Virtual Issues
Vol. 1, Iss. 11 Virtual Journal for Biomedical Optics

Citation
Byoung Chul Ko and Jae-Yeal Nam, "Object-of-interest image segmentation based on human attention and semantic region clustering," J. Opt. Soc. Am. A 23, 2462-2470 (2006)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-23-10-2462

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