Glass Defect Detection Techniques using Digital Image Processing -A Review

Glass defects are a major reason for poor quality and of embarrassment for manufacturers. It is a tedious process to manually inspect very large size glasses. The manual inspection process is slow, time-consuming and prone to human error. Automatic inspection systems using image processing can overcome many of these disadvantages and offer manufacturers an opportunity to significantly improve quality and reduce costs. In this paper we review various glass defects and the possible automated solutions using image processing techniques for defect detection..

[1]  Filippo Attivissimo,et al.  A low-cost inspection system for online defects assessment in satin glass , 2009 .

[2]  Jie Zhao,et al.  A Method for Detection and Classification of Glass Defects in Low Resolution Images , 2011, 2011 Sixth International Conference on Image and Graphics.

[3]  Hyonam Joo,et al.  Detecting low-contrast defect regions on glasses using highly robust model-fitting estimator , 2007, 2007 International Conference on Control, Automation and Systems.

[4]  Filippo Attivissimo,et al.  An automated visual inspection system for the glass industry , 2008 .

[5]  Fan Zhiyong,et al.  Application of Digital Image Process Technology to the Mouth of Beer Bottle Defect Inspection , 2007, 2007 8th International Conference on Electronic Measurement and Instruments.

[6]  Euripides G. M. Petrakis,et al.  A survey on industrial vision systems, applications, tools , 2003, Image Vis. Comput..

[7]  Andre Roussel,et al.  Laser glass inspection system , 1997, Other Conferences.

[8]  Akira Ishii,et al.  Detection of foreign material included in LCD panels , 2000, 2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies.

[9]  Zude Zhou,et al.  An online defects inspection method for float glass fabrication based on machine vision , 2008 .

[10]  M. A. Coulthard Image processing for automatic surface defect detection , 1989 .

[11]  Keun-Ho Rew,et al.  Enhancement of Illumination Irregularity for the 2D Blot Detection Under Low Contrast , 2007 .

[12]  Jae Yeong Lee,et al.  Automatic Detection of Region-Mura Defect in TFT-LCD , 2004, IEICE Trans. Inf. Syst..

[13]  Professor Bruce G. Batchelor,et al.  Intelligent Vision Systems for Industry , 1997, Springer London.