Self-training inspection system for the on-line inspection of printed material

Hal E. Beck; Daniel W. McDonald; Dragana P. Brzakovic

doi:10.1117/12.21199

1 August 1990 Self-training inspection system for the on-line inspection of printed material

Hal E. Beck, Daniel W. McDonald, Dragana P. Brzakovic

Proceedings Volume 1294, Applications of Artificial Neural Networks; (1990) https://doi.org/10.1117/12.21199
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

The system presented in this paper is a self-training visual inspection system that detects and classifies flaws in digitized images of surfaces with known characteristics. The system is composed of a control unit a signalprocessing unit and aclassifier. The control unitmonitors the generation andplacement of simulated flaws learning schedules and provides the teaching signal to the classifier. The signal processing unit simulates an optical area-to-line transformation for high speed processing and extracts regions of interest. The classifier is a multi-layer connectionist neural network. Two inspection tasks are targeted and the system''s performance in each is analyzed in terms of the neural network''s behavior including various learning schedules and application of three diagnostic tools developed in this work. 1.

Citation Download Citation

Hal E. Beck, Daniel W. McDonald, and Dragana P. Brzakovic "Self-training inspection system for the on-line inspection of printed material", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21199

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