Automated Classification of Astronomical Images

Details Automated Classification of Astronomical Images Automated Classification of Astronomical Images

Aug 1995

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1995pasp..107..770o&link_type=abstract

Publications of the Astronomical Society of the Pacific, v.107, p.770

Astronomy and Astrophysics

Astronomy

31

Techniques: Image Processing, Methods: Analytical

Scientific paper

Current efforts to perform automatic image measurement and classification are reviewed. As an example, we discuss the acquisition, calibration, and star-galaxy classification of O and E band imagery from POSS-I obtained with the Minnesota Automated Plate Scanner (APS). For galaxies with isophotal diameters (mu_B = 24.5 mss) larger than 25", it is shown that a variety of two-dimensional photometric parameter spaces provide a crude segregation of Hubble types. Initial results are presented on the training and testing of two artificial neural networks developed to map input image parameter vectors to an 8 step morphological type scale. (SECTION: Stars)

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