Title :
The hierarchical cluster model for image region segmentation
Author :
Randall, Jonathan ; Guan, Ling ; Zhang, Xing ; Li, Wanqing
Author_Institution :
Sydney Univ., NSW, Australia
fDate :
6/24/1905 12:00:00 AM
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;
Conference_Titel :
Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
Print_ISBN :
0-7803-7304-9
DOI :
10.1109/ICME.2002.1035876