Edge detection in noisy images using a water-flow model

Gun-Ill Lee; In-Kwon Kim; Dong-Wook Jung; Jung-Hee Song; Won-Gee Kwak; Rae-Hong Park

doi:10.1117/1.2135782

1 October 2005 Edge detection in noisy images using a water-flow model

Gun-Ill Lee, In-Kwon Kim, Dong-Wook Jung, Jung-Hee Song, Won-Gee Kwak, Rae-Hong Park

Author Affiliations +

Journal of Electronic Imaging, Vol. 14, Issue 4, 043010 (October 2005). https://doi.org/10.1117/1.2135782

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.

©(2005) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Gun-Ill Lee, In-Kwon Kim, Dong-Wook Jung, Jung-Hee Song, Won-Gee Kwak, and Rae-Hong Park "Edge detection in noisy images using a water-flow model," Journal of Electronic Imaging 14(4), 043010 (1 October 2005). https://doi.org/10.1117/1.2135782

Published: 1 October 2005

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