DocumentCode :
3583490
Title :
The hierarchical cluster model for image region segmentation
Author :
Randall, Jonathan ; Guan, Ling ; Zhang, Xing ; Li, Wanqing
Author_Institution :
Sydney Univ., NSW, Australia
Volume :
1
fYear :
2002
fDate :
6/24/1905 12:00:00 AM
Firstpage :
693
Abstract :
The hierarchical cluster model (HCM), a neural network inspired by the human brain (see Sutton, J., Harvard Medical School, MIT, Neural Systems Group, Technical Report, 1995), is demonstrated for the purpose of region segmentation in digital images. Starting with an over segmented image, regions are merged based on evidence of a valid edge between the two regions. Unlike Sutton´s work, in which the HCM is used to recall a set of pre-trained memory patterns, the HCM in our work demonstrates unsupervised decision making capabilities.
Keywords :
decision making; image segmentation; neural nets; pattern clustering; unsupervised learning; hierarchical cluster model; image segmentation; neural network; region segmentation; unsupervised decision making; Australia; Biological system modeling; Biomembranes; Brain modeling; Digital images; Equations; Hopfield neural networks; Humans; Image segmentation; Neurons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
Print_ISBN :
0-7803-7304-9
Type :
conf
DOI :
10.1109/ICME.2002.1035876
Filename :
1035876
Link To Document :
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