Bottle inspector based on machine vision

C. Toxqui-Quitl; J. Cardenas-Franco; A. Padilla-Vivanco; J. Valdiviezo-Navarro

doi:10.1117/12.2008571

6 March 2013 Bottle inspector based on machine vision

C. Toxqui-Quitl, J. Cardenas-Franco, A. Padilla-Vivanco, J. Valdiviezo-Navarro

Proceedings Volume 8661, Image Processing: Machine Vision Applications VI; 86610Y (2013) https://doi.org/10.1117/12.2008571
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

A machine vision system for fault detection in PET bottles is presented. The bottle inspector is divided in three modules for image acquisition of bottle finish, bottle wall and bottle bottom. The captured images are corrected by adaptive gamma correction. An algorithm based in the frequency filtering of n images for defect detection of bottle wall and bottle finish is proposed. We obtain a correct rate classification of 85.5 % in bottle finish, 80.64 % in bottle wall and 95.0 % in bottle bottom.

Citation Download Citation

C. Toxqui-Quitl, J. Cardenas-Franco, A. Padilla-Vivanco, and J. Valdiviezo-Navarro "Bottle inspector based on machine vision", Proc. SPIE 8661, Image Processing: Machine Vision Applications VI, 86610Y (6 March 2013); https://doi.org/10.1117/12.2008571

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