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Proceedings Paper

Intelligent neural network classifier for automatic testing
Author(s): Baoxing Bai; Heping Yu
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Paper Abstract

This paper is concerned with an application of a multilayer feedforward neural network for the vision detection of industrial pictures, and introduces a high characteristics image processing and recognizing system which can be used for real-time testing blemishes, streaks and cracks, etc. on the inner walls of high-accuracy pipes. To take full advantage of the functions of the artificial neural network, such as the information distributed memory, large scale self-adapting parallel processing, high fault-tolerance ability, this system uses a multilayer perceptron as a regular detector to extract features of the images to be inspected and classify them.

Paper Details

Date Published: 3 October 1996
PDF: 5 pages
Proc. SPIE 2899, Automated Optical Inspection for Industry, (3 October 1996); doi: 10.1117/12.253045
Show Author Affiliations
Baoxing Bai, Changchun Institute of Optics and Fine Mechanics (China)
Heping Yu, Changchun Institute of Optics and Fine Mechanics (China)

Published in SPIE Proceedings Vol. 2899:
Automated Optical Inspection for Industry
Frederick Y. Wu; Shenghua Ye, Editor(s)

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