Surface Inspection Using Computer Vision and Gradient Spectrum

Abstract:

This paper is concerned with the problem of automatic inspection of hot-rolled plate surface using computer vision. An automated visual inspection system has been developed to take images of external hot-rolled plate surfaces and an intelligent surface defect detection paradigm based on gradient spectrum technique is presented. Gradient spectrum characterizes the spatial configuration of local image texture and is robust against any monotonic transformation of the gray scale. Texture features based on gradient spectrum are extracted from ROI in hot-rolled plate surface images and integrated into a feature vector which uniquely differentiates the abnormal regions from normal surface. Classification accuracies using the gradient spectrum and gradient-based method are compared. The results indicate that gradient spectrum performs well in classifying the samples with the lowest classification error.

• Periodical: Advanced Materials Research (Volumes 204-210)
• Pages: 1964-1967
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.204-210.1964
• Online since: February 2011
• Authors: Qiang Song
• Keywords: Computer Vision, Gradient Spectrum, Hot-Rolled Plate, Surface Inspection, Texture Analysis

References

[1] R. Rinn and S. A. Thompson: ASIE Steel Tech. Vol. 6 (2000), p.56.

[2] T. Piironen: Mach. Vision Appl. Vol. 3(4) (1990), p.247.

[3] T. Ojala, M. Pietikäinen and T. Mäenpaä: IEEE Trans. Patt. Anal. Mach. Intell. Vol. 24(7) (2002), p.971.

[4] T. Mäenpaä , M. Turtinen, and M. Pietikäinen. Real-Time Imaging (2003), p.289.

[5] G. McLean and M. Jernigan. J. Opt. Soc. Amer. A Vol. 8 (1991), p.141.

[6] A. Rosenfeld and M. Thurston. IEEE Trans. Computers Vol. 20 (1971) p.562.