Title :
Multiple Granularities Self-Modified Method Based on MRF for Image Segmentation
Author :
Zheng, Chen ; Hu, Yijun ; Wang, Leiguang ; Qin, Qianqing
Author_Institution :
Sch. of Math. & Stat., Wuhan Univ., Wuhan, China
Abstract :
In this paper, a multiple granularities self-modified method based on MRF (MGSM-MRF) is proposed for image segmentation. Current segmentation methods are usually focused on a single pixel-based granularity of an image. But the multiple granularities property of an image is limited to the methods using a single granularity. The proposed MGSM-MRF considers the multiple granularities property for image segmentation by incorporating MRF. The advantages of MGSM-MRF include the multiple granularities description for an image and a self-modified method for segmentation by different granularities. Experiments prove a high accuracy and efficiency of MGSM-MRF compared with single pixel-based granularity MRF model.
Keywords :
Markov processes; image segmentation; Markov random field; image segmentation; multiple granularities self-modified method; single pixel-based granularity; Accuracy; Conferences; Equations; Image segmentation; Markov processes; Mathematical model; Pixel;
Conference_Titel :
Wireless Communications Networking and Mobile Computing (WiCOM), 2010 6th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-3708-5
Electronic_ISBN :
978-1-4244-3709-2
DOI :
10.1109/WICOM.2010.5600677