This dataset includes various gauge blocks of different heights at different positions. This includes two sets of data with no targets and different measurement heights. Each data consists of 16 phase-shifting images and their corresponding Gray code images. The processing flow is as follows: first, obtain the unwrapped phases of each group data sequentially through the above images, and then using GRNN neural network to obtain phase offsets at different positions, and substituting them into all unwrapped phases, finally performing phase-to-height mapping on the unwrapped phases that eliminate phase offsets.All data is classified and stored in folders, good luck!
Instructions:
This dataset includes various gauge blocks of different heights at different positions. This includes two sets of data with no targets and different measurement heights. Each data consists of 16 phase-shifting images and their corresponding Gray code images. The processing flow is as follows: first, obtain the unwrapped phases of each group data sequentially through the above images, and then using GRNN neural network to obtain phase offsets at different positions, and substituting them into all unwrapped phases, finally performing phase-to-height mapping on the unwrapped phases that eliminate phase offsets. All data is classified and stored in folders, good luck!
@data{y1mm-j834-24,
doi =
{10.21227/y1mm-j834},
url =
{https://dx.doi.org/10.21227/y1mm-j834},
author =
{Shuhuan Han and Xinjie Li and Xubo Zhao and Yanxi Yang and Xinyu Zhang},
publisher = {IEEE Dataport},
title =
{phase-to-height images},
year =
{2024} }
TY - DATA
T1 -
phase-to-height images
AU -
Shuhuan Han; Xinjie Li; Xubo Zhao; Yanxi Yang; Xinyu Zhang
PY -
2024
PB - IEEE Dataport
UR -
10.21227/y1mm-j834
ER -