Application of Parallel Algorithm in Image Processing of Steel Surfaces for Defect Detection

Mostafa SADEGHI, Hossein SOLTANI, Kamran ZAMANIFAR
1.974 453

Abstract


As the industry of steel manufacturing progresses all over the world, application of image processing has also developed in quality control of products. One of the main problems in image processing of steel surfaces in large volume is performing matrix multiplication. In this paper, we will discuss that by using the algorithm of matrix multiplication in parallel for applying filter on the image of steel surfaces, we are able to detect the defects made on them with higher speed and accuracy.


Keywords


Image Processing, Gabor Wavelet, Quality control, steel process, Parallel Multiplication Matrix

Full Text:

PDF


References


Yazdchi, M., Yazdi, M., Golibagh , A., “Steel Surface Defect Detection Using Texture Segmentation Based on Multifractal Dimension,” The 1nd International Conference on Digital Image Processing (ICDIP 2009), pp. 346-350, 2009.

Chalasani, S., “Segmentation and Performance Evaluation of Steel Defect Images,” Department of Mechanical Engineering, Indian institute of Technology, Kanpur, Master's thesis, 2000.

Guha, P., “Automated Visual Inspection of Steel Surface, Texture Segmentation and Development of a Perceptual Similarity Measure, “ Department of Mechanical Engineering, Indian institute of Technology, Kanpur, Master's thesis, Aprl. 2001.

Yun, P., Park, Y., Seo, B., “Development of Real-time Defect Detection Algorithm for High-speed Steel Bar in Coil (BIC),” SICEICASE International Joint Conference, Busan, Korea, 2006.

Jia, J. H., Murphey, Y., L., “An Intelligent Real-time Vision System for Surface Defect Detection,” Proceedings of the 17th International Conference on Pattern Recognition (ICPR’04).

Yazdchi, M., Golibagh, A., Nazeri, A., “Detection and Classification of Surface Defects of Cold RollinMill Steel Using Morphology and Neural Network,” International Conference on Computational Intelligence for Modelling, Control and Automation (CIMCA 08), pp. 1071-1076, 2008. [7]

Golabpur,A, Kiyani,B, Shaeybani,R, Ahmadiyan,L,. “A new parallel algorithm for matrix multiplication problem, “ 2”national conference on computer science , Sanandaj, Iran, Novomber. 2013.

Bodnarova, A., Williams, J., Bennamoun, M., Kubik, K., “Optimal Textural Features for Flaw Detection in Textile Materials,” In Proceedings of IEEE TENCON’97 Conference, pp. 307–310, 1997.

Conners, R., McMillan, C., Lin, K., “Identifying and Locating Surface Defects in Wood: Part of an Automated Timber Processing System, “ IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 573–583, 1983.

Iivarinen, J., Rauhamaa, J., Visa, A., “Unsupervised Segmentation of Surface Defects,” In International Conference on Pattern Recognition, vol. 4, pp. 356–360, 1996.

Iivarinen, J., “Surface Defect Detection with Histogram-Based Texture Features,” In SPIE Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision, vol. 4197, pp. 140–145, 2000.