Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75264
Title: Solely excitatory oscillator network for color image segmentation
Authors: Li, CL 
Lee, ST 
Issue Date: 2004
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2004, v. 3174, p. 387-392 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: A solely excitatory oscillator network (SEON) is proposed for color image segmentation. SEON utilizes its parallel nature to reliably segment images in parallel. The segmentation speed does not decrease in a very large network. Using NBS distance, SEON effectively segments color images in term of human perceptual similarity. Our model obtains an average segmentation rate of over 98.5%. It detects vague boundaries very efficiently. Experiments show that it segments faster and more accurately than other contemporary segmentation methods. The improvement in speed is more significant for large images.
Description: International Symposium on Neural Networks [ISNN]
URI: http://hdl.handle.net/10397/75264
ISSN: 0302-9743
EISSN: 1611-3349
Appears in Collections:Conference Paper

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