Classification of Ceramic Tiles by Identifying Defect on Ceramic Tile Surface Using Local Texture Feature

Bertalya Bertalya; Prihandoko Prihandoko; Rakhma Oktavina; Yogi Febrianto

doi:10.4028/www.scientific.net/AMR.789.257

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 789Classification of Ceramic Tiles by Identifying...

Classification of Ceramic Tiles by Identifying Defect on Ceramic Tile Surface Using Local Texture Feature

Abstract:

In ceramic tiles industry, the process of ceramics classification plays an important part. At present, the process of classification is carried out manually by using the human eyes observation. However, the capability of the human eyes is very limited. This condition leads to the low accuracy of the ceramic tile selection. This paper proposes a mechanism which could classify the ceramic tiles automatically using local texture feature. The result of our experiment shows a recognition rate of 76%, which means that this method can be used to classify the ceramic tiles.

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Periodical:

Advanced Materials Research (Volume 789)

Pages:

257-261

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.789.257

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Online since:

September 2013

Authors:

Bertalya Bertalya, Prihandoko Prihandoko, Rakhma Oktavina, Yogi Febrianto

Keywords:

Ceramic Tile, Classification, Defect, Texture

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References

[1] Anonymous. Jenis keramik, http: /www. rumahhide. com, (2010).

Google Scholar

[2] H. Elbehiery, A. Hefnawy and M. Elewa. Surface defects detection for ceramic tiles using image processing and morphological techniques,. World Academy of Science, Engineering and Technology. (2005).

Google Scholar

[3] I Novak and Z. Hocenski. Texture feature extraction for a visual inspection of ceramic tiles,. (2003).

DOI: 10.1109/isie.2005.1529109

Google Scholar

[4] X. Xie. A review of recent advances in surface defect detection using texture analysis techniques,. Electonic Letters on Computer Vision and Image Analysis 7(3): 1-22. Computer Vision Center. Spain. (2008).

DOI: 10.5565/rev/elcvia.268

Google Scholar

[5] R.C. Gonzalez & R.E. Woods. Digital image processing second edition, Prentice Hall, New Jersey. (2002).

Google Scholar

[6] R.C. Gonzales, R.E. Woods, and S.L. Eddins. Digital image processing using MATLAB. Pearson Education, India. (2005).

Google Scholar

[7] C. Carson. Blobworld : A system for Region-based Image Indexing and retrieval,. Procs. 3rd Int. Conf. On Visual Information System. Springer-Verlag. Amsterdam, (1999).

Google Scholar