Markerless Image Alignment Method for Pressure-Sensitive Paint Image

Kyosuke Suzuki, Tomoki Inoue, Takayuki Nagata, Miku Kasai, Taku Nonomura, Yu Matsuda*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We propose a markerless image alignment method for pressure-sensitive paint measurement data replacing the time-consuming conventional alignment method in which the black markers are placed on the model and are detected manually. In the proposed method, feature points are detected by a boundary detection method, in which the PSP boundary is detected using the Moore-Neighbor tracing algorithm. The performance of the proposed method is compared with the conventional method based on black markers, the difference of Gaussian (DoG) detector, and the Hessian corner detector. The results by the proposed method and the DoG detector are equivalent to each other. On the other hand, the performances of the image alignment using the black marker and the Hessian corner detector are slightly worse compared with the DoG and the proposed method. The computational cost of the proposed method is half of that of the DoG method. The proposed method is a promising for the image alignment in the PSP application in the viewpoint of the alignment precision and computational cost.

Original languageEnglish
Article number453
JournalSensors
Volume22
Issue number2
DOIs
Publication statusPublished - 2022 Jan 1

Keywords

  • Feature point detection
  • Flow measurement
  • Image alignment
  • Pressure-sensitive paint

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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