Abstract—Due to the complexity of surface texture, the images obtained from the existing online detection system cannot show the strip surface defects exactly, which becomes one of the important problems to be solved for the detection of surface defects of cold-rolled strip. An innovative wavelet-based image filtering algorithm by virtue of anisotropic diffusion is therefore proposed. It decomposes the original image into the low and high-frequency components by wavelet transform, then the high-frequency components are regularized by wavelet diffusion coefficients and, finally, the filtered image is reconstructed by inverse wavelet transform. To achieve a satisfactory filtering result, the wavelet-based anisotropic diffusion is often performed iteratively. Experimental results indicated that this new algorithm could not only filter off the unnecessary texture background unnecessary texture background but also preserve the valuable information in detail effectively. With more favorable combinability in filtering, this algorithm will lay a solid foundation for the subsequent image processing, e.g. image edge detection, image auto-segment, etc.
Index Terms—anisotropic diffusion, defect detection, image filtering, image processing, wavelet transform
Liu Weiwei is with the State Key Laboratory of Rolling & Automation, Northeastern University, China. (Tel: 86-138-8914-4609; e-mail: ghostliuww@gmail.com).
Zhao Jiuliang was with School of Mechanical Engineering and Automation, Northeastern University, China (e-mail: zhaojiuliang@sgqg.com).
Yan Feng was with College of Information Science and Engineering, Northeastern University, China (e-mail: yalephone@163.com).
Yan Yunhui is with School of Mechanical Engineering and Automation, Northeastern University, China (e-mail: yanyh@mail.neu.edu.cn).
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Cite: Liu Weiwei, Zhao Jiuliang, Yan Feng and Yan Yunhui, "An effective Filter Algorithm Approach to Steel Strip Surface Image,"
International Journal of Engineering and Technology vol. 1, no. 3, pp. 204-207, 2009.
