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Automated focusing of an optical microscope
Author(s) -
Kenny L. C.
Publication year - 1983
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.1365-2818.1983.tb04713.x
Subject(s) - focus (optics) , texture (cosmology) , contrast (vision) , microscope , artificial intelligence , computer science , computer vision , position (finance) , microscopy , optical microscope , pattern recognition (psychology) , optics , image (mathematics) , physics , scanning electron microscope , finance , economics
SUMMARY Automated microscope focusing can be seen as a special pattern recognition problem. Current focusing techniques, which identify the optimum focus by its characteristic increase in contrast, have limitations, and the use of texture analysis is suggested as an alternative. Both approaches were tested on two samples of fine particles with very different characteristic images, and several texture parameters were found to indicate optimum focus. Focusing methods suitable for routine use in the analysis of these samples were developed and tested. The spatial content of the texture measurements was found to contribute significantly to the accurate prediction of the optimum focus position, particularly in images lacking contrast.