Design of a Vision Based Bottle Cap Inspection System

Article Preview

Abstract:

Inspection plays a major role in any production process. The acceptance or rejection decision of the production lot depends on the inspection results. In recent years, the developments in machine vision techniques have made inspection easier. This paper aims at bottle cap inspection using machine vision techniques. Bottle neck may have defects such as absence of the cap, absence of the tamper ring and improper assembly of cap and tamper ring. This paper deals with checking of the above mentioned defects with a single image of the finished product. This system uses backlight technique. The image of the product obtained using camera is processed using image processing software and then the results obtained are used to accept or reject the particular product. This technique could be implemented in industries for a batch produced series of bottle coming in a conveyor. By using machine vision techniques it is ensured that not even a single defect related to bottle cap is left from observation. Thus the bottle cap inspection becomes easy, accurate and done in less time.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

917-921

Citation:

Online since:

August 2015

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Yan Tai-shan, Cui Du-wu, The Method of Intelligent Inspection of Product Quality Based on Computer Vision, International Conference on Computer Aided Industrial Design and Conceptual Design, (2006) 1-6.

DOI: 10.1109/caidcd.2006.329469

Google Scholar

[2] E. N. Malamas, E. G. M. Petrakis, M. Zervakisa, L. Petit, and J. Legat, A Survey on Industrial Vision Systems Applications and Tools, Image and Vision Computing. 21(2003) 171–188.

DOI: 10.1016/s0262-8856(02)00152-x

Google Scholar

[3] N Aleixos, J Blasco, E Molto, et al., Assessment of Citrus Fruit Quality using a Real-time Machine Vision System, The 15th International Conference on Pattern Recognition, Barcelona Spain. (2000) 482 -485.

DOI: 10.1109/icpr.2000.905381

Google Scholar

[4] Cheng-Jin Du, Da-Wen Sun, Comparison of Three Methods for Classification of Pizza Topping Using Different Colour Space Transformations, Journal of Food Engineering 68(2005) 277–287.

DOI: 10.1016/j.jfoodeng.2004.05.044

Google Scholar

[5] N.G. Shankar, Z.W. Zhong. Defect Detection on Semiconductor Wafer Surfaces, Microelectronic Engineering 77(2005) 337–346.

DOI: 10.1016/j.mee.2004.12.003

Google Scholar

[6] Leila Yazdi, Anton Satria Prabuwono, Ehsan Golkar, Feature Extraction Algorithm for Fill Level and Cap Inspection in Bottling Machine, International Conference on Pattern Analysis and Intelligent Robotics, Putrajaya, Malaysia (2011) 28-29.

DOI: 10.1109/icpair.2011.5976910

Google Scholar

[7] A. S. Prabuwono, R. Sulaiman, A. R. Hamdan, and Hasniaty A., Development of Intelligent Visual Inspection System (IVIS) for Bottling Machine, Proceedings IEEE TENCON 07. (2007) 1-4.

DOI: 10.1109/tencon.2006.343887

Google Scholar