A classification algorithm for star-galaxy counts

Statistics – Computation

Scientific paper

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Algorithms, Astronomical Catalogs, Astronomical Photography, Classifications, Digital Data, Galaxies, Image Processing, Stars, Black And White Photography, Digital Techniques, Pattern Recognition

Scientific paper

A methodology for image classification developed for faint object discrimination on photographic plates is presented. It is based on the description of textural properties characterizing different categories of objects by gray-tone spatial-dependence matrices. Such matrices are computed from quantized digital subimages centered on the objects to be classified and including a convenient region of surrounding background. Statistical analyses of the co-occurrence matrices referring to preselected training sets of images permit the definition of the classification parameters. The final assignment of each object to a given class is based on objective criteria. The overall procedure requires reasonably short computation times, so that automatic classification of very large samples of objects is feasible.

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