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https://hdl.handle.net/2440/67426
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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: an international journal, 2010; 21(4):403-412 |
Publisher: | Springer-Verlag |
Issue Date: | 2010 |
ISSN: | 0932-8092 1432-1769 |
Statement of Responsibility: | 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 |
DOI: | 10.1007/s00138-008-0171-x |
Published version: | http://dx.doi.org/10.1007/s00138-008-0171-x |
Appears in Collections: | Aurora harvest Computer Science publications |
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