Research Article
PDF EndNote BibTex RIS Cite

A New Gradient Based Surface Defect Detection Method for the Ceramic Tile

Year 2022, Volume 26, Issue 6, 1159 - 1169, 31.12.2022
https://doi.org/10.16984/saufenbilder.1038022

Abstract

Ceramic tiles are controlled to detect surface defects after production because many defects may occur on their surface during production. The detection of ceramic tile surface defects is usually performed by human observations in most factories. In this paper, an image processing method was proposed to detect the defects. In the proposed method, first, the user selects the homogenous region in the image. Then the gradient-based image processing algorithm is applied. We conducted our study using simulated and real images to which we applied the conventional image processing methods and our proposed method. Performance of the proposed method was evaluated with quality metric and subjective evaluation. The obtained results demonstrate that the proposed method has very good performance and is very promising for ceramic tile application.

References

  • [1] M. H. Karimi, D. Asemani, “Surface defect detection in tiling Industries using digital image processing methods: Analysis and evaluation”, ISA transactions, vol. 53, no. 3, pp. 834-844, 2014.
  • [2] T. Czimmermann, G. Ciuti, M. Milazzo, M. Chiurazzi, S. Roccella, C. M. Oddo, P. Dario, “Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY”, Sensors, vol. 20, no. 5, pp. 1459, 2020.
  • [3] G. M. Rahaman, M. Hossain, “Automatic defect detection and classification technique from image: a special case using ceramic tiles”, International Journal of Computer Science and Information Security, vol. 1, no. 1, pp. 22-30, 2009.
  • [4] S. H. Hanzaei, A. Afshar, F. Barazandeh, “Automatic detection and classification of the ceramic tiles’ surface defects”, Pattern Recognition, vol. 66, pp. 174-189, 2017.
  • [5] A. Mohan, S. Poobal, “Crack detection using image processing: A critical review and analysis”, Alexandria Engineering Journal, vol. 57, no. 2, pp. 787-798, 2018.
  • [6] A. N. Shire, M. M. Khanapurkar, R. S. Mundewadikar, “Plain ceramic tiles surface defect detection using image processing”, in 2011 Fourth International Conference on Emerging Trends in Engineering & Technology, pp. 215-220, November 2011.
  • [7] H. F. Ng, “Automatic thresholding for defect detection”, Pattern recognition letters, vol. 27, no. 14, pp. 1644-1649, 2006.
  • [8] Z. Hocenski, T. Keser, A. Baumgartner, “A simple and efficient method for ceramic tile surface defects detection”, in 2007 IEEE International Symposium on Industrial Electronics, pp. 1606-1611, June 2007.
  • [9] A. Sioma, “Automated Control of Surface Defects on Ceramic Tiles Using 3D Image Analysis”, Materials, vol. 13, no.5, pp. 1250, 2020.
  • [10] A. Latif-Amet, A. Ertüzün, A. Erçil, “An efficient method for texture defect detection: sub-band domain co-occurrence matrices”, Image and Vision computing, vol. 18, no. 6-7, pp. 543-553, 2000.
  • [11] S. Vasilic, Z. Hocenski, “The edge detecting methods in ceramic tiles defects detection”, in 2006 IEEE International Symposium on Industrial Electronics, pp. 469-472, July 2006.
  • [12] Z. Hocenski, T. Keser, “Failure detection and isolation in ceramic tile edges based on contour descriptor analysis”, in 2007 Mediterranean Conference on Control & Automation, pp. 1-6, June 2007.
  • [13] Y. C. Samarawickrama, C. D. Wickramasinghe, “Matlab based automated surface defect detection system for ceremic tiles using image processing”, in 2017 6th National Conference on Technology and Management (NCTM), pp. 34-39, January 2017.
  • [14] Matlab, Image Processing Toolbox.
  • [15] I. Sobel, “Camera models and perception”, Ph.D. thesis, Stanford University, CA, 1970.
  • [16] J. Prewitt, “Object Enhancement and Extraction. Picture Processing and Psychopictorics”, NY, Academic Pres., 1970.
  • [17] J. Canny, “A Computational approach to edge detection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, pp. 679-700, 1986.
  • [18] R. C. Gonzalez, R. E. Woods, S. L. Eddins, “Digital Image Processing Using MATLAB”, Saddle River, NJ, Pearson Prentice Hall., 2004.
  • [19] S. Chowdhury, D. Dhara, S. Chowdhury, P. Haldar, K. Chatterjee, T. K. Bhattacharya, “A novel approach toward microstructure evaluation of sintered ceramic materials through image processing techniques”, International Journal of Applied Ceramic Technology, vol. 18, no. 3, pp. 773-780, 2021.

Year 2022, Volume 26, Issue 6, 1159 - 1169, 31.12.2022
https://doi.org/10.16984/saufenbilder.1038022

Abstract

References

  • [1] M. H. Karimi, D. Asemani, “Surface defect detection in tiling Industries using digital image processing methods: Analysis and evaluation”, ISA transactions, vol. 53, no. 3, pp. 834-844, 2014.
  • [2] T. Czimmermann, G. Ciuti, M. Milazzo, M. Chiurazzi, S. Roccella, C. M. Oddo, P. Dario, “Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY”, Sensors, vol. 20, no. 5, pp. 1459, 2020.
  • [3] G. M. Rahaman, M. Hossain, “Automatic defect detection and classification technique from image: a special case using ceramic tiles”, International Journal of Computer Science and Information Security, vol. 1, no. 1, pp. 22-30, 2009.
  • [4] S. H. Hanzaei, A. Afshar, F. Barazandeh, “Automatic detection and classification of the ceramic tiles’ surface defects”, Pattern Recognition, vol. 66, pp. 174-189, 2017.
  • [5] A. Mohan, S. Poobal, “Crack detection using image processing: A critical review and analysis”, Alexandria Engineering Journal, vol. 57, no. 2, pp. 787-798, 2018.
  • [6] A. N. Shire, M. M. Khanapurkar, R. S. Mundewadikar, “Plain ceramic tiles surface defect detection using image processing”, in 2011 Fourth International Conference on Emerging Trends in Engineering & Technology, pp. 215-220, November 2011.
  • [7] H. F. Ng, “Automatic thresholding for defect detection”, Pattern recognition letters, vol. 27, no. 14, pp. 1644-1649, 2006.
  • [8] Z. Hocenski, T. Keser, A. Baumgartner, “A simple and efficient method for ceramic tile surface defects detection”, in 2007 IEEE International Symposium on Industrial Electronics, pp. 1606-1611, June 2007.
  • [9] A. Sioma, “Automated Control of Surface Defects on Ceramic Tiles Using 3D Image Analysis”, Materials, vol. 13, no.5, pp. 1250, 2020.
  • [10] A. Latif-Amet, A. Ertüzün, A. Erçil, “An efficient method for texture defect detection: sub-band domain co-occurrence matrices”, Image and Vision computing, vol. 18, no. 6-7, pp. 543-553, 2000.
  • [11] S. Vasilic, Z. Hocenski, “The edge detecting methods in ceramic tiles defects detection”, in 2006 IEEE International Symposium on Industrial Electronics, pp. 469-472, July 2006.
  • [12] Z. Hocenski, T. Keser, “Failure detection and isolation in ceramic tile edges based on contour descriptor analysis”, in 2007 Mediterranean Conference on Control & Automation, pp. 1-6, June 2007.
  • [13] Y. C. Samarawickrama, C. D. Wickramasinghe, “Matlab based automated surface defect detection system for ceremic tiles using image processing”, in 2017 6th National Conference on Technology and Management (NCTM), pp. 34-39, January 2017.
  • [14] Matlab, Image Processing Toolbox.
  • [15] I. Sobel, “Camera models and perception”, Ph.D. thesis, Stanford University, CA, 1970.
  • [16] J. Prewitt, “Object Enhancement and Extraction. Picture Processing and Psychopictorics”, NY, Academic Pres., 1970.
  • [17] J. Canny, “A Computational approach to edge detection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, pp. 679-700, 1986.
  • [18] R. C. Gonzalez, R. E. Woods, S. L. Eddins, “Digital Image Processing Using MATLAB”, Saddle River, NJ, Pearson Prentice Hall., 2004.
  • [19] S. Chowdhury, D. Dhara, S. Chowdhury, P. Haldar, K. Chatterjee, T. K. Bhattacharya, “A novel approach toward microstructure evaluation of sintered ceramic materials through image processing techniques”, International Journal of Applied Ceramic Technology, vol. 18, no. 3, pp. 773-780, 2021.

Details

Primary Language English
Subjects Engineering, Electrical and Electronic
Journal Section Research Articles
Authors

Murat Alparslan GÜNGÖR> (Primary Author)
HITIT UNIVERSITY, FACULTY OF ENGINEERING, DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING
0000-0001-7446-7808
Türkiye

Publication Date December 31, 2022
Submission Date December 17, 2021
Acceptance Date October 10, 2022
Published in Issue Year 2022, Volume 26, Issue 6

Cite

Bibtex @research article { saufenbilder1038022, journal = {Sakarya University Journal of Science}, eissn = {2147-835X}, address = {}, publisher = {Sakarya University}, year = {2022}, volume = {26}, number = {6}, pages = {1159 - 1169}, doi = {10.16984/saufenbilder.1038022}, title = {A New Gradient Based Surface Defect Detection Method for the Ceramic Tile}, key = {cite}, author = {Güngör, Murat Alparslan} }
APA Güngör, M. A. (2022). A New Gradient Based Surface Defect Detection Method for the Ceramic Tile . Sakarya University Journal of Science , 26 (6) , 1159-1169 . DOI: 10.16984/saufenbilder.1038022
MLA Güngör, M. A. "A New Gradient Based Surface Defect Detection Method for the Ceramic Tile" . Sakarya University Journal of Science 26 (2022 ): 1159-1169 <https://dergipark.org.tr/en/pub/saufenbilder/issue/74051/1038022>
Chicago Güngör, M. A. "A New Gradient Based Surface Defect Detection Method for the Ceramic Tile". Sakarya University Journal of Science 26 (2022 ): 1159-1169
RIS TY - JOUR T1 - A New Gradient Based Surface Defect Detection Method for the Ceramic Tile AU - Murat AlparslanGüngör Y1 - 2022 PY - 2022 N1 - doi: 10.16984/saufenbilder.1038022 DO - 10.16984/saufenbilder.1038022 T2 - Sakarya University Journal of Science JF - Journal JO - JOR SP - 1159 EP - 1169 VL - 26 IS - 6 SN - -2147-835X M3 - doi: 10.16984/saufenbilder.1038022 UR - https://doi.org/10.16984/saufenbilder.1038022 Y2 - 2022 ER -
EndNote %0 Sakarya University Journal of Science A New Gradient Based Surface Defect Detection Method for the Ceramic Tile %A Murat Alparslan Güngör %T A New Gradient Based Surface Defect Detection Method for the Ceramic Tile %D 2022 %J Sakarya University Journal of Science %P -2147-835X %V 26 %N 6 %R doi: 10.16984/saufenbilder.1038022 %U 10.16984/saufenbilder.1038022
ISNAD Güngör, Murat Alparslan . "A New Gradient Based Surface Defect Detection Method for the Ceramic Tile". Sakarya University Journal of Science 26 / 6 (December 2022): 1159-1169 . https://doi.org/10.16984/saufenbilder.1038022
AMA Güngör M. A. A New Gradient Based Surface Defect Detection Method for the Ceramic Tile. SAUJS. 2022; 26(6): 1159-1169.
Vancouver Güngör M. A. A New Gradient Based Surface Defect Detection Method for the Ceramic Tile. Sakarya University Journal of Science. 2022; 26(6): 1159-1169.
IEEE M. A. Güngör , "A New Gradient Based Surface Defect Detection Method for the Ceramic Tile", Sakarya University Journal of Science, vol. 26, no. 6, pp. 1159-1169, Dec. 2022, doi:10.16984/saufenbilder.1038022

Sakarya University Journal of Science (SAUJS)