Paper
23 September 2014 Segmentation of astronomical images
Author Affiliations +
Abstract
Object detection is one of the most important procedures in astronomical imaging. This paper deals with segmentation of astronomical images based on random forrest classifier. We consider astronomical image data acquired using a photometric system with B, V, R and I filters. Each image is acquired in more realizations. All image realizations are corrected using master dark frame and master at field obtained as an average of hundreds of images. Then a profile photometry is applied to find possible position of stars. The classifier is trained by B, V, R and I image vectors. Training samples are defined by user using ellipsoidal regions (20 selections for both classes: object, background). A number of objects and their positions are compared with astronomical object catalogue using Euclidean distance. We can conclude that the performance of the presented technique is fully comparable to other SoA algorithms.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jan Švihlík, Stanislav Vítek, Karel Fliegel, Petr Páta, and Elena Anisimova "Segmentation of astronomical images", Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 921722 (23 September 2014); https://doi.org/10.1117/12.2062009
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

Astronomy

Stars

Image processing algorithms and systems

CCD image sensors

Sensors

Telescopes

RELATED CONTENT

SIFAP2 a new versatile configuration at the TNG for...
Proceedings of SPIE (July 08 2018)
Angular Resolution Requirements For Orbital Astronomy
Proceedings of SPIE (March 24 1970)
High-speed SALT instrument CCD detectors
Proceedings of SPIE (September 29 2004)
Simultaneous seeing measurements at Atacama
Proceedings of SPIE (September 28 2004)

Back to Top