Star Identification Algorithm Based on Image Normalization and Zernike Moments

• Published in: IEEE access Vol. 8; pp. 29228 - 29237
• Main Authors: Liang, Xiaobo, Ma, Wenli, Zhou, Jin, Kong, Sijie
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive optics; Algorithms; Astronomical catalogs; Celestial bodies; Feature extraction; Image normalization; Image rotation; Manganese; Optical imaging; Optical sensors; star identification; Stars; Telescopes; Zernike moment
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.2972568

The star identification (star-ID) algorithm can match the stars captured by an optical system with a star catalog according to certain features. Star-ID has been an important research issue in many astronomical studies and a strong robust star-ID algorithm can effectively identify a certain number of stars as a standard source to correct uncalibrated telescopes. Generally, before star-ID, the celestial coordinates should be translated into the image coordinates with knowledge of optical center coordinates, image rotation angle, focal length of optical system, image sensor's pixel size and so on. For an uncalibrated telescope, the star-ID performance usually suffers from the errors or even the lack of these parameters. In this paper, a novel star-ID algorithm is devised which is based on image normalization technique and the Zernike moment such that the invariant features of asterisms are extracted instead of traditional ways. And three real images which captured via an uncalibrated ground-based telescope are used to validate our method, and the results show that it can effectively identify stars with a success rate of 99.27%, which demonstrate the robustness and accuracy of the proposed method.