Microscope objective camera

facet_spatial_calibration_2022_DEC_20_v2.zip

  • We insert a grid with 1.5mm slits (both open and material part) into the collimated beam and observe this interference pattern:

  • Background subtraction is done using the edges of the image to calculate an average background per pixel

  • Three regions of interest are identified and peaks are fitted

  • The pixel position of these peaks are related to a length calibration: micron per pixel:  0.11108
  • We average over three such images: 0
    mat = scipy.io.loadmat('ProfMon-CAMR_LI20_307-2022-12-17-180149') # 0.111124
    mat = scipy.io.loadmat('ProfMon-CAMR_LI20_307-2022-12-17-180153') # 0.111239
    mat = scipy.io.loadmat('ProfMon-CAMR_LI20_307-2022-12-17-180157') # 0.111079
  • Final result, horizontal: 0.111147 micron per pixel

  • Next, we also consider vertical calibration (after rotating the image by 90 degrees):

  • Result: 0.11175, 0.11196 → 0.111855 micron per pixel
    For simplicity, we use the average value for both: 0.1115 micron per pixel

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