Gabor feature based discriminative dictionary learning for period order detection in fringe projection profilometry

B. Budianto, Pak Kong Lun

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

2 Citations (Scopus)

Abstract

Fringe projection profilometry (FPP) is a popular method for accurate 3D model reconstruction. In a typical FPP process, a tedious phase unwrapping procedure is often needed to obtain the true phase information of the captured fringe images. However, conventional phase unwrapping algorithms often suffer from the ambiguity problems when the scene contains occlusions or sudden jumps in object's height profile. In this paper, we propose an efficient decoding strategy to overcome the ambiguity problems. A novel coded fringe pattern is employed and a Gabor feature based discriminative dictionary is used to estimate the unknown period order of the wrapped phase. Experimental results show that the proposed method can achieve an accurate 3D reconstruction of objects' model in various adverse conditions where traditional FPP methods often fail to perform.
Original languageEnglish
Title of host publication2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015
PublisherIEEE
Pages283-288
Number of pages6
ISBN (Electronic)9789881476807
DOIs
Publication statusPublished - 19 Feb 2016
Event2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015 - Hong Kong, Hong Kong
Duration: 16 Dec 201519 Dec 2015

Conference

Conference2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015
Country/TerritoryHong Kong
CityHong Kong
Period16/12/1519/12/15

ASJC Scopus subject areas

  • Artificial Intelligence
  • Modelling and Simulation
  • Signal Processing

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