Neural network correction of ultrasonic C-scan images.
A neural network-based approach to the correction of C-scan images is presented. This allows the effects of a finite ultrasonic beam diameter in an immersion experiment to be considered, by training the network on a series of defects of known characteristics. The result is an image which is a better representation of the actual defect.
Hutchins
D A
DA
Department of Engineering, University of Warwick, Coventry, UK. dah@eng.warwick.ac.uk
Pardoe
A C
AC
Billson
D R
DR
Hines
E L
EL
D006801:Humans; D007089:Image Enhancement; D016571:Neural Networks, Computer; D014465:Ultrasonics