Second Derivative Gaussian Algorithm in Engine Fault Image

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Abstract:

In this paper, we proposed an improved Second Derivative Gaussian (SDG); the endoscopic image of the engine fault was treated by a combination of wavelet and improved SDG, in order to enhance the quality of the image and denosing. The results shows that the propose method can reduce the noise and improve the detail of the image. Provide support for further diagnosis.

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769-772

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December 2011

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[1] Somsak Choomchuay, Keokanlaya Sihalath, an Application of Second Derivative of Gaussian Filters in Fingerprint Image Enhancement, (2010).

DOI: 10.1109/icbbe.2010.5518074

Google Scholar

[2] MENG LIBIN, ZHAO JINCHUANG, FU WENLI, an Improved Fingerprint Enhancement Algorithm Based on Gabor Filter. (2006).

Google Scholar

[3] Yunlin LUO, Yilong ZHANG, Diagnosis of Aero-engine's Endoscope Faults Based on a New Fuzzy Connectedness, (2009).

DOI: 10.1109/ccdc.2010.5498472

Google Scholar

[4] Roberto H. Bamberger, a Filter Bank for the Directional Decomposition of Images: Theory and Design, IEEE TRANSACTIONS ON SIGNALPROCESS. (1992).

Google Scholar

[5] Yuichi Tanaka, Masaaki Ikehara, Multiresolution Image Representation Using Combined 2-D and 1-D Directional Filter Banks, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 18, NO. 2, FEBRUARY (2009).

DOI: 10.1109/tip.2008.2008078

Google Scholar

[6] SU Jin Shan, FENG Yan, A novel DFB of multiresolution and its design.

Google Scholar

[7] Fingerprint Image Enhancement with Second Derivative Gaussian Filter and Directional WaveletTransform, Keokanlaya Sihalath, Somsak Choomchuay, 2010 Second International Conference on Computer Engineering and Application.

DOI: 10.1109/iccea.2010.178

Google Scholar