Calibration of uncooled long wavelength infrared imagers - BC-388
Preferred Disciplines: Engineering Physics, Physics, Electrical Engineering, Mechanical Engineering, Computer Engineering/Science (Masters, PhD, Post-Doc)
Project length: 4-6 months (1 unit)
Approx. start date: As soon as possible
Location: Vancouver, BC
No. of Positions: 1
Preferences: UBC / SFU
Company: EIO Diagnostics
EIO Diagnostics combines multispectral imaging with machine learning to the problem of early detection of dairy animal udder infections (mastitis).
Summary of Project:
EIO Diagnostics combines multispectral imaging with machine learning to the problem of early detection of dairy animal udder infections (mastitis). The infrared imagers we are using are uncooled microbolometers which are sensitive to internal imager temperature and environment temperature. Dairy animal udder surface temperatures are sensitive to environment temperature and health of the udder. While our algorithms attempt to reduce the effect of these sensitivities we would like to eliminate them.
We would like to implement published solutions in this space and compare the results to a radiometric camera from the same manufacturer.
Background and required skills
- Literature search to establish calibration methods and materials
- Implementation of calibration method
- Comparison of calibrated non-radiometric imager to radiometric imager
Expertise and Skills Needed:
- Imaging and optics: basic knowledge of long wave infrared light and its behaviour
- Software development in C or Python, on Ubuntu or Raspberry Pi
- Access to environmental chamber with programmable ambient air temperature control (10°C to 30°C) and blackbody sources with temperatures from 10°C to 50°C.
For more info or to apply to this applied research position, please