DocumentCode :
508174
Title :
Image Contour Extraction Based on CNN and Active Contour Model
Author :
Xiao-hua, Liu ; Da, Yuan ; Jin-Jiang, Li
Author_Institution :
Dept. of Electron. Eng., Naval Aeronaut. Eng. Acad., Yantai, China
Volume :
2
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
14
Lastpage :
17
Abstract :
A CNN is a dynamic nonlinear system with the local connectivity of cells and easy to be translated into a VLSI implementation. CNNs are very suitable for modeling the physical process of energy propagation since CNNs conserve the physical properties of a continuous structure. For the contour extraction, this paper proposes a method for establishing the evolution model of active contour by CNN technique. Further,the relationship between CNNs and the minimization for active contour model is investigated and the derivation of the CNN implementations for converting the active contour model to CNN templates is performed in order to improve the computing efficiency. Experimental results are given to demonstrate the feasibility of the proposed method in extracting contour from the blurred edge and high-noise images.
Keywords :
cellular neural nets; edge detection; feature extraction; image segmentation; CNN technique; VLSI implementation; active contour model minimization; blurred edge images; cellular neural network; connected neural network; dynamic nonlinear system; energy propagation process; high-noise images; image contour extraction; Active contours; Aerodynamics; Aerospace engineering; Cellular neural networks; Computer science; Iterative methods; Nonlinear dynamical systems; Nonlinear systems; Partial differential equations; Stability; Active Contour Model; CNN; Contour extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.86
Filename :
5365814
Link To Document :
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