Fourier interpolation and neural network analysis for accurate 3D reconstruction of images produced by an inductive sensor

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper describes a novel methodology to reduce the scanning time and to extract bar dimensional information from images generated by an inductive sensor. Using a sparsely populated data set obtained from a reduced number of scan lines, faster high resolution images are generated using image interpolation techniques. Having generated these images, image filtering, peak picking and neural networks methods are applied to extract bar dimensional information and accurate 3 D visualization.

Bibliographical metadata

Original languageEnglish
Title of host publicationReview of Progress in Quantitative Nondestructive Evaluation Volume 24
Pages836-843
Number of pages8
Volume760
DOIs
Publication statusPublished - 9 Apr 2005
EventReview of Progress in Quantitative Nondestructive Evaluation - Golden, CO, United States
Event duration: 25 Jul 200430 Jul 2004

Conference

ConferenceReview of Progress in Quantitative Nondestructive Evaluation
CountryUnited States
CityGolden, CO
Period25/07/0430/07/04