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General Information
    • ISSN: 1793-8198 (Print)
    • Abbreviated Title: Int. J. Mater. Mech. Manuf.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMMM
    • Editor-in-Chief: Prof. Ian McAndrew
    • Co-editor-in-Chief: Prof. K. M. Gupta
    • Executive Editor: Cherry L. Chen
    • Abstracting/Indexing: Inspec (IET), Chemical Abstracts Services (CAS),  ProQuest, Crossref, Ulrich's Periodicals Directory,  EBSCO.
    • E-mail ijmmm@ejournal.net

Prof. Ian McAndrew
Capitol Technology University, USA
It is my honor to be the editor-in-chief of IJMMM. I will do my best to work with the editorial team and help make this journal better.

IJMMM 2015 Vol.3(3): 170-173 ISSN: 1793-8198
DOI: 10.7763/IJMMM.2015.V3.189

Glass Surface Defects Detection with Wavelet Transforms

Bayram Akdemir and Şaban Öztürk
Abstract—Nowadays, the increasing population increases the consumption as well. Manufacturing systems are developing in a fast pace to meet increasing demand of consumption. However, very quick increase of production has surpassed the development speed of currently existing control systems. In manufacturing, since the quality is a very important issue as well as the quantity, the operation of quality control systems must be accelerated and must be accomplished by machines. The idea of our study is based on this thinking. Especially defect detection on widely used glass material that is extremely difficult to accomplish by humans can be implemented in a quick, accurate and stable way. In the presented method, various defects like scratches, bubbles, cracks, corrosion on the glass surface can be identified. Glass images obtained from a homogenously illuminated medium are processed by wavelet transform and obtained images from the wavelet transform are denoised. Finally, Shannon threshold method is applied to the images. From the obtained results, defects like scratches, bubbles on the surface of the glass can be detected successfully.

Index Terms—Glass defect detection, texture analysis, image processing, wavelet transform, machine vision.

The authors are with the Electrical and Electronics Engineering Department, Engineering Faculty, University of Selcuk, Konya, Turkey (e-mail: {bayakdemir, sabanozturk}@selcuk.edu.tr).


Cite: Bayram Akdemir and Şaban Öztürk, "Glass Surface Defects Detection with Wavelet Transforms," International Journal of Materials, Mechanics and Manufacturing vol. 3, no. 3, pp. 170-173, 2015.

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