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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Industrial and Systems Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
