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http://dx.doi.org/10.5391/JKIIS.2002.12.5.467

A study on FCNN structure based on a α-LTSHD for an effective image processing  

Byun, Oh-Sung (원광대학교 전기ㆍ전자 및 정보공학부)
Moon, Sung-Ryong (원광대학교 전기ㆍ전자 및 정보공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.12, no.5, 2002 , pp. 467-472 More about this Journal
Abstract
In this paper, we propose a Fuzzy Cellular Neural Network(FCNN) that is based on a-Least Trimmed Square Hausdorff distance(a-LTSHD) which applies Hausdorff distance(HD) to the FCNN structure in order to remove the impulse noise of images effectively and also improve the speed of operation. FCNN incorporates Fuzzy set theory to Cellular Neural Network(CNN) structure and HD is used as a scale which computes the distance between set or two pixels in binary images without confrontation of the feature object. This method has been widely used with the adjustment of the object. For performance evaluation, our proposed method is analyzed in comparison with the conventional FCNN, with the Opening-Closing(OC) method, and the LTSHD based FCNN by using Mean Square Error(MSE) and Signal to Noise Ratio(SNR). As a result, the performance of our proposed network structure is found to be superior to the other algorithms in the removal of impulse noise.
Keywords
FCNN; Hausdorff Distance; $\alpha$-Least Trimmed Square; OC; MSE;
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