Regional fringe analysis for improving depth measurement in phase-shifting fringe projection profilometry

Kuang Che Chang Chien, Han Yen Tu, Ching Huang Hsieh, Chau Jern Cheng, Chun Yen Chang

Research output: Contribution to journalArticle

1 Citation (Scopus)


This study proposes a regional fringe analysis (RFA) method to detect the regions of a target object in captured shifted images to improve depth measurement in phase-shifting fringe projection profilometry (PS-FPP). In the RFA method, region-based segmentation is exploited to segment the de-fringed image of a target object, and a multi-level fuzzy-based classification with five presented features is used to analyze and discriminate the regions of an object from the segmented regions, which were associated with explicit fringe information. Then, in the experiment, the performance of the proposed method is tested and evaluated on 26 test cases made of five types of materials. The qualitative and quantitative results demonstrate that the proposed RFA method can effectively detect the desired regions of an object to improve depth measurement in the PS-FPP system.

Original languageEnglish
Article number015007
JournalMeasurement Science and Technology
Issue number1
Publication statusPublished - 2018 Jan



  • Phase-shifting
  • classifcation
  • depth measurement
  • fringe projection proflometry
  • fuzzy analysis
  • region-based segmentation

ASJC Scopus subject areas

  • Instrumentation
  • Engineering (miscellaneous)
  • Applied Mathematics

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