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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
