DocumentCode
1791334
Title
Fast joint optimization in MRF-MAP-based segmentation of color images
Author
Zhao Qiyang ; Li Weibo
Author_Institution
State Key Lab. of Software, Beihang Univ., Beijing, China
fYear
2014
fDate
14-16 Oct. 2014
Firstpage
387
Lastpage
391
Abstract
Color image segmentation is an important topic in the image processing field. In most segmentation methods based on MRF-MAP, the segmentation quality is far behind requirement due to the absence of appearance models, and it is often suffering from the low computational efficiency of iterated calculations. To address these problems, the paper proposes a new segmentation method for color images based on MRF-MAP, which is solved approximately in an efficient non-iterated way, with the help of a slightly tuned Lanczos eigensolver. The experiments demonstrate that the new method achieves competitive performance compared with the groundtruths or other state-of-the-art methods.
Keywords
Markov processes; eigenvalues and eigenfunctions; image colour analysis; image segmentation; maximum likelihood estimation; optimisation; Lanczos eigensolver; MRF-MAP; color image segmentation method; fast joint optimization; image processing; iterated calculation; maximum a posteriori on Markov random field; segmentation quality; Approximation methods; Color; Computational modeling; Computer vision; Image color analysis; Image segmentation; Markov processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing (CISP), 2014 7th International Congress on
Conference_Location
Dalian
Type
conf
DOI
10.1109/CISP.2014.7003811
Filename
7003811
Link To Document