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    Practical Examples of Useful Algorithms in Computer-Aided Microscopy

    Published: 01 January 1991

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    The primary goal of computer-aided microscopy is to collect the best possible microscope image, manipulate this image into its accurate binary components of interest, and then analyze the binary structure from an analytical, statistical point-of-view.

    Poor sample preparation, low feature contrast, or nonuniform lighting require that the operator enhance the image prior to performing the quantitative analysis. There are many transformations by which microscopists can interact with the computer to alter an image. Qualitative enhancement can be achieved through such algorithms as histogram stretching, contrast enhancement, image contouring and spatial filtering. These operations alter intensity values of particular pixels in an image. Operations which use spatial or geometric transformations allow the operator to interact with the image analyzer and quantitatively alter the image.

    A selection of image processing techniques will be presented to describe the mathematical basis for gray level and binary image transformations in computer-aided microscopy. Examples from the materials sciences will be used to demonstrate how the various techniques are applied.


    computer-aided microscopy, image analysis, image enhancement

    Author Information:

    Cole, GS
    Research Staff, Ford Motor Company, Dearborn, MI

    Committee/Subcommittee: E04.03

    DOI: 10.1520/STP17256S