Paper
19 May 1992 Syntactic approach to the segmentation and classification of morphological features of galaxies
Alberto Accomazzi
Author Affiliations +
Proceedings Volume 1657, Image Processing Algorithms and Techniques III; (1992) https://doi.org/10.1117/12.58357
Event: SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, 1992, San Jose, CA, United States
Abstract
Most of the information related to the morphology of galaxies relies on the presence, shape and texture of patterns such as bars, rings, and spiral arms. Automatic classification of astronomical images requires therefore that objects represented in the image are indexed by the recognition of such morphological structures. We describe a methodology to segment well- known images of galaxies in their morphological features in an automated fashion. The detection, description and classification of these features is achieved through the use of attributed rewriting systems that allow the identification of structures according to rules formalizing the interpretation strategy followed by astronomers in the visual classification of galaxies. A priori knowledge about the physical characteristics of the objects in the image, as well as the image acquisition process controls the interpretation activity of the automated system allowing the design of flexible algorithms that can be tailored to a wide range of images differing in resolution, noise characteristics, and object orientation. Some results obtained applying the system to CCD images of spiral galaxies are presented.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alberto Accomazzi "Syntactic approach to the segmentation and classification of morphological features of galaxies", Proc. SPIE 1657, Image Processing Algorithms and Techniques III, (19 May 1992); https://doi.org/10.1117/12.58357
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Galactic astronomy

Image segmentation

Image processing

Image classification

Hubble Space Telescope

Astronomy

Classification systems

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