Surface Defects Detection for Ceramic Tiles UsingImage Processing and Morphological Techniques
Quality control in ceramic tile manufacturing is hard, labor intensive and it is performed in a harsh industrial environment with noise, extreme temperature and humidity. It can be divided into color analysis, dimension verification, and surface defect detection, which is the main purpose of our work. Defects detection is still based on the judgment of human operators while most of the other manufacturing activities are automated so, our work is a quality control enhancement by integrating a visual control stage using image processing and morphological operation techniques before the packing operation to improve the homogeneity of batches received by final users.
[1] Vincent LEBRUN, "Quality control of ceramic tiles by machine
vision," Flaw Master 3000, Surface Inspection Ltd. 2001.
[2] C. Boukouvalas, J Kittler, R Marik, M Mirmehdi and M Petrou,
"Ceramic Tile Inspection for Color and Structural defects." I.E.E.E.
Transactions on Pattern Analysis and Machine Intelligence, vol. 14,
no. 1, March 1998.
[3] Stewart Coe, "Automatic tile inspection." Surface Inspection Limited,
International Ceramics, Bristol, U.K., Issue 1, 2000.
[4] Costas Boukouvalas, Francesco De Natale, Josef Kittler, and Roberto
Salgrai. "An Integrated system for Quality Inspection of tiles."
University of Surrey, Guilford, GU2-5XH, England, 1999.
[5] Yonghuai Liu and Macros Rodrigues, "A novel machine vision
algorithm for a fast response quality control system." Department of
Computer Science, the University of Hull, Hull, HU6 7RX, UK 2001.
[6] Martin Coulthard, "Measuring and Classifying Tile Shades."
Chairman, Surface Inspection Ltd, Great Britain, Jan., 2001.
[7] Song K Y, Petrou M, and Kittler, "Texture crack detection." Machine
Vision Applications, to appear Jan., 1995.
[8] Esko Herrala, "SIMON; Spectral Imaging for On line Sorting."
Specim, Spectral Imaging Ltd., Finland, August 1998.
[9] Tony Lindeberg, "Edge Detection and Ridge Detection with Automatic
Scale Selection." Department of Numerical Analysis and Computing
Science, Royal Institute of Technology, International Journal of
Computer Vision, S-10044 Stockholm, Sweden, Jan., 1996.
[10] Mark E. Lehr and Keh-Shin Li, "Template basis techniques to Pattern
recognition." University of California Riverside, Department of
Statistics Riverside, California, USA, Vol. 2825, 1996.
[11] Todd Reed and H. Wechsler, "Segmentation of textured images and
gestalt organization using spatial / spatial-frequency representations."
I.E.E.E. Transactions on Pattern Analysis and Machine Intelligence,
vol. 12, no. 1 Jan., 1990.
[12] W. Wen, and A. Xia, "Verifying Edges for visual Inspection
Purposes." School of Mechanical and Manufacturing Engineering,
School of Mathematics, The University of New South Wales, NSW
2052, Australia, July 1997.
[13] Simon Baker, "Design and Evaluation of Feature Detectors." Doctor
of philosophy thesis in the Graduate School of Arts and Sciences,
Columbia University, 1998.
[14] Richard Bridge, "Computer Image Processing." Tessella support
services PLC, Oxon, England, Issue V1.R2.M0, June, 2003.
[1] Vincent LEBRUN, "Quality control of ceramic tiles by machine
vision," Flaw Master 3000, Surface Inspection Ltd. 2001.
[2] C. Boukouvalas, J Kittler, R Marik, M Mirmehdi and M Petrou,
"Ceramic Tile Inspection for Color and Structural defects." I.E.E.E.
Transactions on Pattern Analysis and Machine Intelligence, vol. 14,
no. 1, March 1998.
[3] Stewart Coe, "Automatic tile inspection." Surface Inspection Limited,
International Ceramics, Bristol, U.K., Issue 1, 2000.
[4] Costas Boukouvalas, Francesco De Natale, Josef Kittler, and Roberto
Salgrai. "An Integrated system for Quality Inspection of tiles."
University of Surrey, Guilford, GU2-5XH, England, 1999.
[5] Yonghuai Liu and Macros Rodrigues, "A novel machine vision
algorithm for a fast response quality control system." Department of
Computer Science, the University of Hull, Hull, HU6 7RX, UK 2001.
[6] Martin Coulthard, "Measuring and Classifying Tile Shades."
Chairman, Surface Inspection Ltd, Great Britain, Jan., 2001.
[7] Song K Y, Petrou M, and Kittler, "Texture crack detection." Machine
Vision Applications, to appear Jan., 1995.
[8] Esko Herrala, "SIMON; Spectral Imaging for On line Sorting."
Specim, Spectral Imaging Ltd., Finland, August 1998.
[9] Tony Lindeberg, "Edge Detection and Ridge Detection with Automatic
Scale Selection." Department of Numerical Analysis and Computing
Science, Royal Institute of Technology, International Journal of
Computer Vision, S-10044 Stockholm, Sweden, Jan., 1996.
[10] Mark E. Lehr and Keh-Shin Li, "Template basis techniques to Pattern
recognition." University of California Riverside, Department of
Statistics Riverside, California, USA, Vol. 2825, 1996.
[11] Todd Reed and H. Wechsler, "Segmentation of textured images and
gestalt organization using spatial / spatial-frequency representations."
I.E.E.E. Transactions on Pattern Analysis and Machine Intelligence,
vol. 12, no. 1 Jan., 1990.
[12] W. Wen, and A. Xia, "Verifying Edges for visual Inspection
Purposes." School of Mechanical and Manufacturing Engineering,
School of Mathematics, The University of New South Wales, NSW
2052, Australia, July 1997.
[13] Simon Baker, "Design and Evaluation of Feature Detectors." Doctor
of philosophy thesis in the Graduate School of Arts and Sciences,
Columbia University, 1998.
[14] Richard Bridge, "Computer Image Processing." Tessella support
services PLC, Oxon, England, Issue V1.R2.M0, June, 2003.
@article{"International Journal of Information, Control and Computer Sciences:64175", author = "H. Elbehiery and A. Hefnawy and M. Elewa", title = "Surface Defects Detection for Ceramic Tiles UsingImage Processing and Morphological Techniques", abstract = "Quality control in ceramic tile manufacturing is hard, labor intensive and it is performed in a harsh industrial environment with noise, extreme temperature and humidity. It can be divided into color analysis, dimension verification, and surface defect detection, which is the main purpose of our work. Defects detection is still based on the judgment of human operators while most of the other manufacturing activities are automated so, our work is a quality control enhancement by integrating a visual control stage using image processing and morphological operation techniques before the packing operation to improve the homogeneity of batches received by final users.
", keywords = "Quality control, Defects detection, Visual control,Image processing, Morphological operation", volume = "1", number = "5", pages = "1488-5", }
