Title :
Image segmentation via multi-scaled belief propagation
Author :
Chen, Shifeng ; Qiao, Yu
Author_Institution :
Shenzhen Institutes of Adv. Technol., CAS, Shenzhen, China
Abstract :
Image segmentation plays an important role in computer vision and image analysis. In this paper, we develop a novel algorithm which can automatically segment an image into regions with relative uniform texture or color without the need to decide the region number in advance. In this work, the segmentation is formulated as a labeling problem in the Markov random fields (MRFs) model. An efficient multi-scale belief propagation (BP) algorithm is used to find the solution to the MRF estimation. Extensive experiments have shown the effectiveness of our approach.
Keywords :
Markov processes; computer vision; image colour analysis; image segmentation; MRF estimation; Markov random field model; computer vision; image analysis; image segmentation; labeling problem; multiscaled belief propagation algorithm; relative uniform color; relative uniform texture; Algorithm design and analysis; Clustering algorithms; Computer vision; Estimation; Image segmentation; Markov processes; Pixel; belief propagation; image segmentation;
Conference_Titel :
Information and Automation (ICIA), 2011 IEEE International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4577-0268-6
Electronic_ISBN :
978-1-4577-0269-3
DOI :
10.1109/ICINFA.2011.5949123
