DocumentCode
1082276
Title
An integration scheme for image segmentation and labeling based on Markov random field model
Author
Kim, Il.Y. ; Yang, Hyun S.
Author_Institution
Micro Devices Business, Samsung Electronics Co. Ltd., Buchun, South Korea
Volume
18
Issue
1
fYear
1996
fDate
1/1/1996 12:00:00 AM
Firstpage
69
Lastpage
73
Abstract
This paper presents a unified approach for the image understanding problem based on the Markov random field models. In the proposed scheme, the image segmentation and interpretation processes cooperate in the simultaneous optimization process so that the erroneous segmentation and misinterpretation can be compensatedly recovered by continuous estimation of the unified energy function
Keywords
Markov processes; computer vision; image recognition; image segmentation; optimisation; Markov random field model; image interpretation; image labeling; image recognition; image segmentation; image understanding; optimization; region clustering; unified energy function; Computer vision; Graphics; Image processing; Image recognition; Image segmentation; Labeling; Layout; Markov random fields; Pattern analysis; Robots;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.476014
Filename
476014
Link To Document