Noncooperative Target Detection of Spacecraft Objects Based on Artificial Bee Colony Algorithm

Xinyu Liu, Donghui Li, Na Dong, Wai Hung Ip, Kai Leung Yung

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)


Although heuristic algorithms have achieved the state-of-the-art performance for object detection, they have not been demonstrated to be sufficiently accurate and robust for multiobject detection. To address this problem, this article incorporates the concept of species into the artificial bee colony algorithm and proposes a multipeak optimization algorithm named species-based artificial bee colony (SABC). Then, we apply SABC to detect the noncooperative target (NCT) from two aspects: Multicircle detection and multitemplate matching. Experiments are conducted using real cases of ShenZhou8 and Apollo 9 space missions as well as the Chang'e camera point system developed by the Hong Kong Polytechnic University. Experimental results show that the proposed method is robust to detect NCT under various kinds of noise, weak light, and in-orbit and leads to accurate detection results with less time than other methods.

Original languageEnglish
Article number8778767
Pages (from-to)3-15
Number of pages13
JournalIEEE Intelligent Systems
Issue number4
Publication statusPublished - 1 Jul 2019

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Artificial Intelligence


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