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Editor-in-chief

 
Faculty of Science, University of Brunei Darussalam, Brunei Darussalam   
" It is a great honor to serve as the editor-in-chief of IJIEE. I'll work together with the editorial team. Hopefully, IJIEE will be recognized among the readers in the related field."
IJIEE 2013 Vol.2(6): 932-935 ISSN: 2010-3719
DOI: 10.7763/IJIEE.2012.V2.244

Mura Region Detection by Using 2D FFT with Exponential Kernel for Black Resin-Coated Steel

Nam Kyu Kwon, Jong Seok Lee, and Poo Gyeon Park

Abstract—This paper proposes mura region detection algorithm by using two-dimensional fast Fourier transform (2D FFT) with exponential kernel for black resin-coated steel. If the mura exists in the black resin-coated steel image, the image has large low-frequency component. To improve accuracy, multiply exponential kernel to low frequency region. The simulation results show improved performance.

Index Terms—2D FFT, defect detection, black resin-coated steel, mura.

The authors are with the Division of Department of Electrical and Computer Engineering and IT Convergence Engineering, Pohang University of Science and Technology, Pohang, Gyungbuk, Republic of Korea (e-mail: kwunnam@postech.ac.kr, jongseoklee@postech.ac.kr,ppg@postech.ac.kr).

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Cite: Nam Kyu Kwon, Jong Seok Lee, and Poo Gyeon Park, "Mura Region Detection by Using 2D FFT with Exponential Kernel for Black Resin-Coated Steel," International Journal of Information and Electronics Engineering vol. 2, no. 6, pp. 923-925, 2012.

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