A-Track: A new approach for detection of moving objects in FITS images

作者：Atay T^*; Kaplan M; Kilic Y; Karapinar N

来源：Computer Physics Communications, 2016, 207: 524-530.

DOI：10.1016/j.cpc.2016.07.023

• Line detection
• Minor planets
• Asteroids
• Image processing

We have developed a fast, open-source, cross-platform pipeline, called A-Track, for detecting the moving objects (asteroids and comets) in sequential telescope images in FITS format. The pipeline is coded in Python 3. The moving objects are detected using a modified line detection algorithm, called MILD. We tested the pipeline on astronomical data acquired by an SI-1100 CCD with a 1-meter telescope. We found that A-Track performs very well in terms of detection efficiency, stability, and processing time. The code is hosted on GitHub under the GNU GPL v3 license.
Program summary
Program title: A-TRACK
Catalogue identifier: AFBC_v1_0
Program summary URL: http://cpc.cs.qub.ac.ukisummaries/AFBC_v1_0.html
Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland
Licensing provisions: GNU General Public Licence Version 3
No. of lines in distributed program, including test data, etc.: 313100
No. of bytes in distributed program, including test data, etc.: 89443558
Distribution format: tar.gz
Programming language: Python 3.
Computer: Personal Computer.
Operating system: Any OS where Python 3 and subprograms are installed.
Classification: 14.
External routines: Numpy, Pandas, SExtractor, PyFITS, Alipy, f2n, docopt, Imagemagick, git-all, scipy, matplatlib, astroasciidata.
Nature of problem: Asteroid and comet detection.
Solution method: A multiple image line detection algorithm for sequential FITS images.

• 出版日期2016-10