Computer vision methods for optical microscopes

  • Authors:

  • M. Boissenin;J. Wedekind;A. N. Selvan;B. P. Amavasai;F. Caparrelli;J. R. Travis

  • Affiliations:

  • Microsystems and Machine Vision Laboratory, Materials and Engineering Research Institute, Sheffield Hallam University, Pond Street, Sheffield S1 1WB, UK;Microsystems and Machine Vision Laboratory, Materials and Engineering Research Institute, Sheffield Hallam University, Pond Street, Sheffield S1 1WB, UK;Microsystems and Machine Vision Laboratory, Materials and Engineering Research Institute, Sheffield Hallam University, Pond Street, Sheffield S1 1WB, UK;Microsystems and Machine Vision Laboratory, Materials and Engineering Research Institute, Sheffield Hallam University, Pond Street, Sheffield S1 1WB, UK;Microsystems and Machine Vision Laboratory, Materials and Engineering Research Institute, Sheffield Hallam University, Pond Street, Sheffield S1 1WB, UK;Microsystems and Machine Vision Laboratory, Materials and Engineering Research Institute, Sheffield Hallam University, Pond Street, Sheffield S1 1WB, UK

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2007

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Abstract

As the fields of micro- and nano-technology mature, there will be an increased need to build tools that are able to work in these areas. Industry will require solutions for assembling and manipulating components, much as it has done in the macro range. With this need in mind, a new set of challenges requiring novel solutions have to be met. One of them is the ability to provide closed-loop feedback control for manipulators. We foresee that machine vision will play a leading role in this area. This paper introduces a technique for integrating machine vision into the field of micro-technology including two methods, one for tracking and one for depth reconstruction under an optical microscope.