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Mathematical Problems in Engineering
Volume 2016, Article ID 5797654, 12 pages
Research Article

Detection of Surface Defects on Steel Strips Based on Singular Value Decomposition of Digital Image

School of Electronic Information Engineering, Taiyuan University of Science and Technology, 66 Waliu Road, Wanbailin District, Taiyuan, Shanxi Province 030024, China

Received 27 April 2016; Accepted 11 October 2016

Academic Editor: José A. Sanz-Herrera

Copyright © 2016 Qianlai Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Image segmentation technology has been widely used to detect the surface defects in metal industries effectively. In some fields of the manufacturing industry, the determination of defects is more concerned than the accurate location and shape of defects. However, most of current image segmentation algorithms are complex or have difficulty determining the defect. This paper presents a novel method for determining and roughly locating the surface defects of steel strips based on Singular Value Decomposition. The method has no need of image segmentation. The gray level matrix of a digital image is projected on its singular vectors obtained by Singular Value Decomposition. A defect is reflected as a sudden change on the projections. Therefore, the defects can be determined and roughly located according to the sudden changes. The experimental results suggest that this method is valid and convenient for determining the surface defects directly.