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Reseach Article

An Automated Tiles Defect Detection

by V. Mohan, S. Suresh Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 109 - Number 11
Year of Publication: 2015
Authors: V. Mohan, S. Suresh Kumar
10.5120/19234-0993

V. Mohan, S. Suresh Kumar . An Automated Tiles Defect Detection. International Journal of Computer Applications. 109, 11 ( January 2015), 24-27. DOI=10.5120/19234-0993

@article{ 10.5120/19234-0993,
author = { V. Mohan, S. Suresh Kumar },
title = { An Automated Tiles Defect Detection },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 109 },
number = { 11 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 24-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume109/number11/19234-0993/ },
doi = { 10.5120/19234-0993 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:44:32.565347+05:30
%A V. Mohan
%A S. Suresh Kumar
%T An Automated Tiles Defect Detection
%J International Journal of Computer Applications
%@ 0975-8887
%V 109
%N 11
%P 24-27
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

It presents an automatic defect identification system for detecting crack of titles from captured digital images based on defect classification and segmentation. Image classification will be used for automated visual inspection to classify defect and protects from quality one. It will be performed through textures analysis and probabilistic neural network. The textures are extracted using wavelet filters with cooccurrence features. The defect detection process involves the preprocessing, segmentation and morphological filtering to make processing system more flexible with accuracy.

References
  1. R. C. Gonzalez, R. E. Woods, "Digital Image Processing", Pearson Education (Singapore), Pte. Ltd. , Indian Branch, 482 F. I. E, Partapgang, 2005 2006.
  2. Md. Maidul Islam, Md. RowshanSahriar and Md. Belal Hossain ?An Enhanced Automatic Surface and Structural Flaw Inspection and Categorization using Image Processing Both for Flat and Textured Ceramic Tiles?, International Journal of Computer Applications (0975 – 888)Volume 48– No. 3, June 2012.
  3. H. Elbehiery, A. Hefnawy, and M. Elewa ?Surface Defects Detection for Ceramic Tiles Using Image Processing and Morphological Techniques?, PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY VOLUME 5 APRIL 2005 ISSN 1307-6884.
  4. Tahir Cetin ?The Defect Detection in Ceramic Materials Basedon Time-Frequency Analysis by Using the Methodof Impulse Noise?, ARCHIVES OF ACOUSTICS DOI: 10. 2478/v10168-011-0007-y36, 1, 77–85 (2011).
  5. Xien Cheng and JinghuaZheng ?Novel Approach of Surface Unfolding for Ceramic Bowls?, I. J. Engineering and Manufacturing 2011, 3, 1-6.
  6. Jean-Luc Bouchot, GernotStubland Bernhard Moser ?A template matching approach based on the discrepancynorm for defect detection on regularly textured surfaces?, https://www. academia. edu.
  7. Ibrahiem M. M. El Emary and S. Ramakrishnan ?On the Application of Various Probabilistic Neural Networks in Solving Different Pattern Classification Problems?, World Applied Sciences Journal 4 (6): 772-780, 2008 ISSN 1818-4952.
  8. Yu Tao, VallipuramMuthukkumarasamy, BrijeshVerma and Michael Blumenstein ?A Texture Feature Extraction Technique Using 2D– DFT and Hamming Distance?, Computational Intelligence and Multimedia Applications, 2003. ICCIMA 2003. Proceedings. Fifth International Conference on 27-30 Sept. 2003.
  9. Yang Mingqiang, KpalmaKidiyo and Ronsin Joseph ?A Survey of Shape Feature Extraction Techniques?, IETR-INSA, UMR-CNRS 6164, 35043 Rennes, Shandong University, 250100, Jinan.
  10. Roberto Márcio de Andrade and Alexandre Carlos Eduardo ?Methodology for Automatic Process of the Fired Ceramic Tile's Internal Defect Using IR Images and Artificial Neural Network?, Methodology for Automatic Process of the Fired Ceramic Tile's Internal Defect Using IR Images and Artificial Neural Network January-March 2011, Vol. XXXIII, No. 1 / 67.
  11. AndrzejMaterka and Michal Strzelecki ?Texture Analysis Methods – A Review?, A. Materka, M. Strzelecki, Texture Analysis Methods – A Review, TechnicalUniversity of Lodz, Institute of Electronics, COST B11 report, Brussels 1998.
Index Terms

Computer Science
Information Sciences

Keywords

Wavelet decomposition Cooccurrence features extraction PNN(Probabilistic Neural Network with Radial basis Function) Segmentation and MATlab.