Title: Automated surface defect detection for cold-rolled steel strip based on wavelet anisotropic diffusion method
Authors: Weiwei Liu; Yunhui Yan
Addresses: School of Mechanical Engineering, Dalian University of Technology, Dalian, 116024, China ' School of Mechanical Engineering and Automation, Northeastern University, Shenyang, 110819, China
Abstract: Taking advantage of digital image processing technology, automatic inspection for surface defects of cold-rolled steel strips promises real-time restriction and is preferable to human inspectors. 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. A novel wavelet-based image filtering algorithm by virtue of anisotropic diffusion filtering is proposed in this paper. The algorithm is divided into four steps: wavelet decomposition, coefficient normalisation of wavelet diffusion, wavelet reconstruction, and edge detection. Experimental results indicated that the method could not only filter off the unnecessary texture background but also preserve the valuable information in detail effectively.
Keywords: wavelet transform; anisotropic diffusion; defect detection; digital image processing; surface defects; surface texture; image filtering; automatic inspection; object recognition; edge detection; cold-rolled steel strip.
International Journal of Industrial and Systems Engineering, 2014 Vol.17 No.2, pp.224 - 239
Available online: 29 May 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article