Automated surface defect detection for cold-rolled steel strip based on wavelet anisotropic diffusion method Online publication date: Fri, 25-Jul-2014
by Weiwei Liu; Yunhui Yan
International Journal of Industrial and Systems Engineering (IJISE), Vol. 17, No. 2, 2014
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Industrial and Systems Engineering (IJISE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook