DocumentCode
2625510
Title
Markov random field based image labeling with parameter estimation by error backpropagation
Author
Kim, Y., II ; Yang, Hyun S.
Author_Institution
Dept. of Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea
fYear
1991
fDate
18-21 Nov 1991
Firstpage
962
Abstract
The authors investigate a method of efficiently labeling images using the Markov random field (MRF). The MRF model is defined on the region adjacency graph and the labeling is then optimally determined using simulated annealing. The MRF model parameters are automatically estimated using an error backpropagation network. The proposed method is analyzed through experiments using real natural scene images
Keywords
Markov processes; neural nets; parameter estimation; pattern recognition; simulated annealing; Markov random field based image labeling; error backpropagation; error backpropagation network; neural nets; parameter estimation; pattern recognition; real natural scene images; region adjacency graph; simulated annealing; Backpropagation; Computer errors; Image recognition; Image segmentation; Indexing; Labeling; Layout; Markov random fields; Parameter estimation; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN
0-7803-0227-3
Type
conf
DOI
10.1109/IJCNN.1991.170524
Filename
170524
Link To Document