DocumentCode :
2395818
Title :
Integrated segmentation of noisy image based on the spatial relationship
Author :
Nguyen, Thanh Minh ; Wu, Q. M Jonathan
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Windsor, Windsor, ON, Canada
fYear :
2012
fDate :
19-20 May 2012
Firstpage :
206
Lastpage :
210
Abstract :
In this paper, we propose a new algorithm for an integrated image segmentation based on the combination of both Markov Random Fields (MRF) and Graph Cuts (GC). In the well-known GrabCut method, the T-link weights do not take into account the spatial relationship between the neighboring pixels. The proposed algorithm, unlike GrabCut method, incorporates this spatial relationship right into the T-link weights. The performance results obtained using natural images clearly demonstrate the robustness, accuracy and effectiveness of the proposed algorithm, as compared to other known methods.
Keywords :
Markov processes; graph theory; image segmentation; GC; GrabCut method; MRF; Markov random fields; T-link weights; graph cuts; integrated image segmentation; natural images; neighboring pixels; noisy image; spatial relationship; Accuracy; Computational modeling; Gaussian noise; Image segmentation; Markov random fields; Object segmentation; Standards; Integrated image segmentation; Markov Random Fields and Graph Cuts;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4673-0198-5
Type :
conf
DOI :
10.1109/ICSAI.2012.6223469
Filename :
6223469
Link To Document :
بازگشت