Fault detection by a Gaussian neural network with reject options in glass bottle production

Christian Firmin; D. Hamad; Jack-Gerard Postaire; Ruo Dan Zhang

doi:10.1117/12.248536

26 August 1996 Fault detection by a Gaussian neural network with reject options in glass bottle production

Christian Firmin, D. Hamad, Jack-Gerard Postaire, Ruo Dan Zhang

Proceedings Volume 2785, Vision Systems: New Image Processing Techniques; (1996) https://doi.org/10.1117/12.248536
Event: Lasers, Optics, and Vision for Productivity in Manufacturing I, 1996, Besancon, France

Abstract

During the production of translucent glass bottles, many inspection procedures are realized in order to eliminate defects which produce dangerous consequences for customs. Checks on the neck of a bottle, which look like cracks in the glass, are one of the most important defects. Although an automated visual inspection system has been developed to solve this specific problem, its ability to cope with variations of the environment is limited and it requires careful tuning whenever the characteristics of the production change. In this paper, we propose a new approach based on computer vision and artificial neural network for check detection. The inspection procedure involves extracting features images of necks, the selection of the most discriminant features, and the decision is realized by a Gaussian neural network with reject options.

Citation Download Citation

Christian Firmin, D. Hamad, Jack-Gerard Postaire, and Ruo Dan Zhang "Fault detection by a Gaussian neural network with reject options in glass bottle production", Proc. SPIE 2785, Vision Systems: New Image Processing Techniques, (26 August 1996); https://doi.org/10.1117/12.248536

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available