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Proceedings Paper

Unsupervised color image segmentation using a dynamic color gradient thresholding algorithm
Author(s): Guru Prashanth Balasubramanian; Eli Saber; Vladimir Misic; Eric Peskin; Mark Shaw
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Paper Abstract

We propose a novel algorithm for unsupervised segmentation of color images. The proposed approach utilizes a dynamic color gradient thresholding scheme that guides the region growing process. Given a color image, a weighted vectorbased color gradient map is generated. Seeds are identified and a dynamic threshold is then used to perform reliable growing of regions on the weighted gradient map. Over-segmentation, if any, is addressed by a Similarity Measurebased region merging stage to produce the final segmented image. Comparative results demonstrate the effectiveness of this algorithm for color image segmentation.

Paper Details

Date Published: 18 February 2008
PDF: 9 pages
Proc. SPIE 6806, Human Vision and Electronic Imaging XIII, 68061H (18 February 2008); doi: 10.1117/12.766184
Show Author Affiliations
Guru Prashanth Balasubramanian, Rochester Institute of Technology (United States)
Eli Saber, Rochester Institute of Technology (United States)
Vladimir Misic, Thomas Jefferson Univ. (United States)
Eric Peskin, Rochester Institute of Technology (United States)
Mark Shaw, Hewlett-Packard Co. (United States)


Published in SPIE Proceedings Vol. 6806:
Human Vision and Electronic Imaging XIII
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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