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A New Edge Detection Using Decomposition Model
International Journal of Intelligent Information Systems
Volume 5, Issue 3-1, May 2016, Pages: 28-31
Received: Dec. 19, 2015; Accepted: Dec. 25, 2015; Published: Jun. 30, 2016
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Saloua Senhaji, Department of Physics, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed ben Abdellah University, Fes, Morocco
Abdellah Aarab, Department of Physics, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed ben Abdellah University, Fes, Morocco
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Edge detection is one of the most commonly used operations in image analysis, and there are more algorithms in the literature for enhancing and detecting edges. Natural images contain both textured and untextured regions, so the cues of contour and texture are exploited simultaneously. In this paper, we present a new edge detection method for natural images using decomposition model. The main idea is to decompose image in to two image components (geometric and texture) obtained by the PDE. The edge detection is performed not on the original image but on its geometric components. Experimental results on a wide range of images are shown.
Partial Differential Equations, EDP, Decomposition Model, Geometrical Component, Edge Detector
To cite this article
Saloua Senhaji, Abdellah Aarab, A New Edge Detection Using Decomposition Model, International Journal of Intelligent Information Systems. Special Issue: Smart Applications and Data Analysis for Smart Cities. Vol. 5, No. 3-1, 2016, pp. 28-31. doi: 10.11648/j.ijiis.s.2016050301.14
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This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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