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Stereo Light Microscope Calibration for 3D Submicron Vision

G. Danuser
Proceedings of the 18th ISPRS Congress
July 1996


The rapid development in micro- and nanotechnology has introduced new challenges to photogrammetry and computer vision. Microscopic imagery has to be seriously investigated by these communities. This paper represents a first step in this direction. It addresses the calibration of Stereo Light Microscopes. Various new aspects have to be investigated when trying to develop computer vision and photogrammetric approaches for this type of sensor. Normally, in macroscopic imagery the contrast and image quality can be controlled to some degree. Due to poor contrast and worse quality of the microscopic imagery the reliable and precise localization of image coordinates becomes a much more difficult task. A high level vision algorithm followed by a modified Least Squares Template Matching adequately solves these problems. In addition, a new imaging model for Stereo Light Microscopy is introduced. It is based on the weak perspective situation in microscopy and includes a new distortion term describing the non paraxial imaging of a Stereo Light Microscope. The results of various calibration runs demonstrate the suitability of this new approach. The new model is explicitly compared with the performance of standard imaging models used in computer vision and photogrammetry, when applying them to microscopy. Relative accuracies of laterally $1:1000$ and vertically $2:100$ are obtained in the object space. In contrast, the relative accuracy in the image space reaches $2:10000$. The discrepancy between the relative accuracies in object and image space results from the limited precision of the underlying calibration standard.

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  author = {G. Danuser},
  title = {Stereo Light Microscope Calibration for 3D Submicron Vision},
  booktitle = {Proceedings of the 18th ISPRS Congress},
  year = {1996},
  month = {July},
  pages = {101-108},
  volume = {XXXI},
  keywords = {stereo microscopy, calibration, bundle, adjustment}