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Edge detection in noisy images using a water-flow model

[+] Author Affiliations
Gun-Ill Lee

Sogang University, Department of Electronic Engineering, C.P.O. Box 1142, Seoul 100-611, South Korea

In-Kwon Kim

Sogang University, Department of Electronic Engineering, C.P.O. Box 1142, Seoul 100-611, South Korea

Dong-Wook Jung

Sogang University, Department of Electronic Engineering, C.P.O. Box 1142, Seoul 100-611, South Korea

Jung-Hee Song

Sogang University, Department of Media Technology, Graduate School of Media Communications, C.P.O. Box 1142, Seoul 100-611, South Korea

Won-Gee Kwak

Sogang University, Department of Electronic Engineering, C.P.O. Box 1142, Seoul 100-611, South Korea

Rae-Hong Park

Sogang University, Department of Electronic Engineering, C.P.O. Box 1142, Seoul 100-611, South Korea

J. Electron. Imaging. 14(4), 043010 (November 28, 2005). doi:10.1117/1.2135782
History: Received September 04, 2004; Revised April 26, 2005; Accepted May 04, 2005; Published November 28, 2005; Online November 28, 2005
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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.

© 2005 SPIE and IS&T

Citation

Gun-Ill Lee ; In-Kwon Kim ; Dong-Wook Jung ; Jung-Hee Song ; Won-Gee Kwak, et al.
"Edge detection in noisy images using a water-flow model", J. Electron. Imaging. 14(4), 043010 (November 28, 2005). ; http://dx.doi.org/10.1117/1.2135782


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