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Edge detection in petrographic images
Author(s) -
STARKEY J.,
SAMANTARAY A. K.
Publication year - 1993
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.1365-2818.1993.tb03421.x
Subject(s) - microscope , pixel , edge detection , grain boundary , optics , artificial intelligence , computer vision , polarizer , smoothing , microscopy , gaussian , geology , image processing , computer science , materials science , physics , image (mathematics) , birefringence , quantum mechanics , metallurgy , microstructure
Summary The automatic detection of mineral grain boundaries in images obtained from a polarized‐light microscope requires special techniques. Observations in both plane‐ and cross‐polarized light may be necessary and the section must be rotated relative to the plane of polarization of the microscope to see all the grain boundaries. In computer‐based microscopy this can be accomplished by the sequential accumulation of individual images captured from one microscope field of view with different polarizer orientations. For real‐time implementation the sequential images are segmented individually by applying Canny's algorithm. A separable Gaussian mask is used for smoothing and a 3 times 3 convolution mask is used to generate 1‐pixel‐wide boundaries, which are located at the zero‐crossing of the second‐order derivative of the intensity gradient. The boundaries are extracted and accumulated in a composite image. The resulting composite image is a synoptic grain‐boundary image of the rock.