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https://hdl.handle.net/2440/67414
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Type: | Conference paper |
Title: | Color image labelling using linear programming |
Author: | Shen, C. Wen, Z. |
Citation: | Proceedings of the 9th International Conference on Digital Image Computing: Techniques and Applications (DICTA'07), 3-5 December, 2007; pp.239-244 |
Publisher: | IEEE |
Publisher Place: | Online |
Issue Date: | 2007 |
ISBN: | 0769530672 |
Conference Name: | Digital Image Computing Techniques and Applications (9th : 2007 : Glenelg, South Australia) |
Statement of Responsibility: | Li Hongdong, Shen Chunhua and Wen Zhiying |
Abstract: | This paper describes a linear programming (LP) algorithm for labelling (segmenting) a color image into multiple regions. Compared with the recently-proposed semi-definite programming (SDP) relaxation based algorithm, our algorithm has a simpler mathematical formulation, and a much lower computational complexity. In particular, to segment an image of M × N pixels into k classes, our algorithm requires only O((M N k)m) complexity--a sharp contrast to the complexity of O((M N k)2n ) offered by the SDP algorithm, where m and n are the polynomial degrees-of- complexity of the corresponding LP solver and SDP solver, respectively (in general we have m n). Moreover, LP has a significantly better scalability than SDP generally. This dramatic reduction in complexity 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 30 × 30 pixels in a few hours, our algorithm can process larger color image of, say, 100 × 100 500 × 500 image in a much shorter time. |
Rights: | © Copyright 2007 IEEE – All Rights Reserved |
DOI: | 10.1109/DICTA.2007.4426802 |
Published version: | http://dx.doi.org/10.1109/dicta.2007.4426802 |
Appears in Collections: | Aurora harvest 5 Computer Science publications |
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