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http://dx.doi.org/10.5391/JKIIS.2004.14.4.473

Adaptive morphological Wavelet-CNN Algorithm for the Color Image Edge detection  

Beak, Young-Hyun (원광대학교 전자공학과)
Moon, Sung-Rung (원광대학교 전자공학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.14, no.4, 2004 , pp. 473-480 More about this Journal
Abstract
This paper presents a new edge detection algorithm in color image. The proposed Adaptive morphological Wavelet-CNN algorithm is divided into two parts : The Adaptive morpholog and WCNN(Wavelet Cellular Neural Networks). It detects the optimal edge with applying this color image to WCNN algorithm, after it does level up a boundary side of a color image by using the adaptive morphology as the threshold of an input color image. Also, it is used not a conventional fixed mask edge detection method but variable mask method which is called a variable BBM. Finally, to show the feasibility of the proposed algorithm, this paper provides by simulation that the color image consists of 30.
Keywords
morphology; CNN; wavelet; edge; threshold; color image;
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