DocumentCode :
2229048
Title :
Extracting long contour by using the competitive layer model of the Lotka-Volterra recurrent neural networks
Author :
Zhen, Bochuan ; Yi, Zhang
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Volume :
3
fYear :
2010
fDate :
20-22 Aug. 2010
Abstract :
It is well known that contours in image are salient when a series of edge elements are aligned in a collinear or co-circular fashion. In this paper, a contour extractor is constructed to extract contours by using the competitive layer mode implemented by Lotka-Volterra recurrent neural networks. This extractor can bind all edge elements which belong to a contour onto a layer. In order to extract long contours, by moving the established contour extractor along a long contour, then the long contour can be extracted segment by segment. Experiments show that the proposed method can extract long contour properly from images.
Keywords :
feature extraction; image segmentation; recurrent neural nets; Lotka-Volterra recurrent neural networks; competitive layer model; edge elements; image segmentation; long contour extraction; Competitive Layer Model; Contour Extracting; Lotka-Volterra Recurrent Neural Networks; Salient Contour;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
ISSN :
2154-7491
Print_ISBN :
978-1-4244-6539-2
Type :
conf
DOI :
10.1109/ICACTE.2010.5579569
Filename :
5579569
Link To Document :
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