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Type: Journal article
Title: Interactive color image segmentation with linear programming
Author: Li, H.
Shen, C.
Citation: Machine Vision and Applications, 2010; 21(4):403-412
Publisher: Springer-Verlag
Issue Date: 2010
ISSN: 0932-8092
Statement of
Hongdong Li, Chunhua Shen
Abstract: 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)2n ) 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.
Keywords: Interactive image segmentation; Linear programming; Object cutout
Rights: © Springer-Verlag 2008
RMID: 0020112698
DOI: 10.1007/s00138-008-0171-x
Appears in Collections:Computer Science publications

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