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Journal of Electronic Imaging

Edge detection in noisy images using a water-flow model
Author(s): Gun-Ill Lee; In-Kwon Kim; Dong-Wook Jung; Jung-Hee Song; Won-Gee Kwak; Rae-Hong Park
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Paper Abstract

We present an edge detection method based on a water-flow model and gradient information. The gradient magnitude image emphasizes edges of objects in an image and effective extraction of well-defined and connected edges having large gradient values follows. The proposed method can be classified as a locally adaptive thresholding method. To show the effectiveness of the proposed method, its simulation results for various noise-free and noisy synthetic and real images are compared with those of conventional methods. In addition, edge evaluation results of five edge detection methods are shown quantitatively.

Paper Details

Date Published: 1 October 2005
PDF: 19 pages
J. Electron. Imag. 14(4) 043010 doi: 10.1117/1.2135782
Published in: Journal of Electronic Imaging Volume 14, Issue 4
Show Author Affiliations
Gun-Ill Lee, Sogang Univ. (South Korea)
In-Kwon Kim, Sogang Univ. (South Korea)
Dong-Wook Jung, Sogang Univ. (South Korea)
Jung-Hee Song, Sogang Univ. (South Korea)
Won-Gee Kwak, Sogang Univ. (South Korea)
Rae-Hong Park, Sogang Univ. (South Korea)

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