Defects Detection of Cold-roll Steel Surface Based on MATLAB
Abstract
The measure of detecting the surface edge information of cold-roll steel sheets has been investigated rely on the digital image processing toolbox of the mathematic software MATLAB, and the edge detecting experiment of surface grayscale image has been conducted on the computer. The method of detecting defects such as black flecks and scratching has been realized in the research, the different effect of operators with the disturbance of noise has been compared, the performance of the LOG's edge detection ability various due to the change of the parameter Sigma. Conclusions have been made that LOG operator maintains the satisfying performance with the disturbance of noise, smaller Sigma is, less satisfying the smoothing ability is, which maintains more details, whereas the smoothing ability is better with loss of more details, defects detection of cold-roll steel surface based on MATLAB has a quite satisfying performance.
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LoG with sigma = 2 provided a better segmentation result.
“LoG with sigma =2 provided better segmentation result.”
From Review of vision-based steel surface inspection systems (2014) · cites this paper as [52]
Six gradient operators (Sobel, Prewitt, Kirsch, Canny, Laplacian and Laplacian of Gaussian) in the spatial domain were tried and compared for a set of images of cold-rolled strips in [52].
“Yichi et al. [52]: In an interesting experiment, six (Sobel, Prewitt, Kirsch, Canny, Laplacian and Laplacian of Gaussian (LoG)) gradient operators in spatial domain, using MATLAB, have been tried and compared for a set of images of cold-rolled strips.”
From Review of vision-based steel surface inspection systems (2014) · cites this paper as [52]
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Review of vision-based steel surface inspection systems
Neogi, N., Mohanta, D. K., & Dutta, P. K. (2014) · EURASIP Journal on Image and Video Processing · doi:10.1186/1687-5281-2014-50 · Cited by 322 · see citing works
“[52]: In an interesting experiment, six (Sobel, Prewitt, Kirsch, Canny, Laplacian and Laplacian of Gaussian (LoG)) gradient operators in spatial domain, using MATLAB, have been tried and compared for a set of images of cold-rolled strips.”
MethodDefect detection of steel surface using entropy segmentation
Nand, G. K., Noopur, & Neogi, N. (2014) · 2014 Annual IEEE India Conference (INDICON) · doi:10.1109/indicon.2014.7030439 · Cited by 44 · see citing works
- Authors
- Yichi, Z., Lv, W., & Xuedong, L.
- Affiliations
- Wuhan University of Technology (CN)
- ORCID
- Venue
- 2011 Third International Conference on Measuring Technology and Mechatronics Automation
- Publisher
- IEEE
- Published
- 2011-01
- Pages
- 827-830
- OpenAlex
- W2145356027
- Cited by
- 6
- References
- 0
- Citations by year
- 2024: 1 · 2019: 1 · 2018: 1 · 2017: 1 · 2014: 2
- FWCI
- 1.85
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Object Detection Techniques
- Physical Sciences › Engineering › Mechanical Engineering › Non-Destructive Testing Techniques
- Keywords
- cold-rolled steel, surface defect detection, edge detection, LOG operator, scratching behavior, noise robustness, sigma parameter, grayscale images, image smoothing
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