Interactive color image segmentation with linear programming

Image segmentation is an important and fundamental task for image and vision understanding. This paper describes a linear programming (LP) approach for segmenting a color image into multiple regions. Compared with the recently proposed semi-definite programming (SDP)-based approach, our approach has...

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Bibliographic Details
Published in:Machine vision and applications Vol. 21; no. 4; pp. 403 - 412
Main Authors: Li, Hongdong, Shen, Chunhua
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer-Verlag 01.06.2010
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ISSN:0932-8092, 1432-1769
Online Access:Get full text
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Summary:Image segmentation is an important and fundamental task for image and vision understanding. This paper describes a linear programming (LP) approach for segmenting a color image into multiple regions. Compared with the recently proposed semi-definite programming (SDP)-based approach, our approach has a simpler mathematical formulation, and a far lower computational complexity. In particular, to segment an image of M  × N pixels into k classes, our method requires only O (( M N k ) m ) complexity—a sharp contrast to the complexity of O (( M N k ) 2 n ) if the SDP method is adopted, where m and n are the polynomial complexity of the corresponding LP solver and SDP solver, respectively (in general we have m ≪ n ). Such a significant reduction in computation readily enables our algorithm to process color images of reasonable sizes. For example, while the existing SDP relaxation algorithm is only able to segment a toy-size image of, e.g., 10 × 10 to 30 × 30 pixels in hours time, our algorithm can process larger color image of, say, 100 × 100 to 500 × 500 image in much shorter time.
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ISSN:0932-8092
1432-1769
DOI:10.1007/s00138-008-0171-x