Robust single-shot fringe pattern projection for three-dimensional measurements

Budianto, Pak Kong Lun, Weiping Zhu

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

Abstract

Although single-shot fringe projection profilometry (FPP) techniques are known to allow effective 3-dimensional measurements (3D) of moving objects, their robustness is often of concern particularly if the object has vivid textures on its surface. Besides, traditional approaches only focus on 3D measurements but ignore the need in many applications of mapping the 3D measurements to the 2-dimensional (2D) textures of the object. In this paper, we present a novel single-shot FPP technique for measuring the 3D model of an object and at the same time estimating its 2D textures. The proposed technique employs a morphological component analysis (MCA) method to separate the fringe patterns and object textures from a fringe image. To further improve the efficiency in identifying the fringe pattern and object texture coefficients, a spatially adaptive thresholding method is developed for MCA. Experimental results show that the proposed technique can significantly improve the robustness of single-shot FPP techniques even when the object has vivid textures on its surface. Besides, it can simultaneously generate the 2D texture image of the object which can hardly be achieved by the traditional single-shot FPP approaches.
Original languageEnglish
Title of host publication2017 22nd International Conference on Digital Signal Processing, DSP 2017
PublisherIEEE
Volume2017-August
ISBN (Electronic)9781538618950
DOIs
Publication statusPublished - 3 Nov 2017
Event2017 22nd International Conference on Digital Signal Processing, DSP 2017 - London, United Kingdom
Duration: 23 Aug 201725 Aug 2017

Conference

Conference2017 22nd International Conference on Digital Signal Processing, DSP 2017
CountryUnited Kingdom
CityLondon
Period23/08/1725/08/17

Keywords

  • 3-dimensional measurement
  • Fringe pattern projection
  • morphological component analysis
  • wavelets

ASJC Scopus subject areas

  • Signal Processing

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