Neural hypercolumn architecture for the preprocessing of radiographic weld images

Alain Gaillard; Donald C. Wunsch II; Richard A. Escobedo

doi:10.1117/12.21189

1 August 1990 Neural hypercolumn architecture for the preprocessing of radiographic weld images

Alain Gaillard, Donald C. Wunsch II, Richard A. Escobedo

Proceedings Volume 1294, Applications of Artificial Neural Networks; (1990) https://doi.org/10.1117/12.21189
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

A general neural hypercolumn architecture is applied to radiographic weld images to locate regions of strong spatial intensity gradients. The hypercolumn output provides information on both the direction and the orientation of local spatial intensity gradients. These outputs can also be used to form an enhanced decimated image which can be processed for feature recognition. Parametric tuning of the architecture is discussed with particular emphasis on the requirements of the application. The performance of this architecture is compared with that of Sobel filters and other edge-detecting convolution masks. The possible representation of these various discrete convolution masks -including hypercolumns - as generalized non-adaptive neurons is also discussed. 1.

Citation Download Citation

Alain Gaillard, Donald C. Wunsch II, and Richard A. Escobedo "Neural hypercolumn architecture for the preprocessing of radiographic weld images", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21189

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