Fast subpixel digital image correlation using artificial neural networks

M. C. Pitter, C. W. See, Michael Geoffrey Somekh

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

8 Citations (Scopus)

Abstract

Digital image correlation has been used to measure microscopic deformation in thermally stressed microelectronics devices. Displacement precisions of better than 0.03 pixels have been achieved by combining nonintegral pixel shifting of subimages and artificial neural networks (ANNs). The ANNs are trained to estimate the subpixel element of the object displacement from the digital correlation. Although similar accuracies can be obtained by curve-fitting to the correlation peaks and differentiating, the neural approach has the advantage that it allows fast subpixel displacement analysis over a range of object textures without knowledge of the analytical form of the correlation peaks.
Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing
Pages901-904
Number of pages4
Publication statusPublished - 1 Jan 2001
Externally publishedYes
EventIEEE International Conference on Image Processing (ICIP) - Thessaloniki, Greece
Duration: 7 Oct 200110 Oct 2001

Conference

ConferenceIEEE International Conference on Image Processing (ICIP)
CountryGreece
CityThessaloniki
Period7/10/0110/10/01

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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