Deep learning based period order detection in structured light three-dimensional scanning

Budianto, Wicky Law, Daniel P.K. Lun

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

5 Citations (Scopus)

Abstract

Fringe projection profilometry (FPP) is a popular optical 3-dimensional (3D) scanning method. However, existing FPP methods often suffer from the ambiguity problem that only the wrapped phase information can be measured while the true phase information is required for 3D measurement. Although various phase unwrapping methods were suggested to recover the wrapped phase in FPP methods, most of them will fail when the target objects have complex structures. To solve this problem, we propose in this paper to embed the fringe pattern with a set of textural patterns to encode the period order of the true phase information. During the offline phase, a convolutional neural network (CNN) is trained to learn a set of filters that will be activated when they see the code patterns. When the encoded fringe image is captured, the modified morphological component analysis is first performed to extract the code pattern. It is then decoded by the trained CNN to estimate the K-map, which contains the period order of the true phase information. Experimental results show that the proposed method can measure the 3D profile of objects with abrupt jumps in height profile, where the conventional approaches often fail to perform. It also has a much higher computational efficiency due to the effective utilization of GPU by CNN.

Original languageEnglish
Title of host publication2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728103976
DOIs
Publication statusPublished - 2019
Event2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Sapporo, Japan
Duration: 26 May 201929 May 2019

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2019-May
ISSN (Print)0271-4310

Conference

Conference2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019
Country/TerritoryJapan
CitySapporo
Period26/05/1929/05/19

Keywords

  • Deep neural network
  • Fringe projection profilometry
  • Structured light 3D scanning

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this