Title: Bacterial foraging-based SIFT for full moon image direction estimation

Authors: Liyong Ma; Yong Zhang

Addresses: School of Information and Electrical Engineering, Harbin Institute of Technology, Weihai, China ' Department of Civil Engineering, Harbin Institute of Technology, Weihai, China

Abstract: Recently as a standalone configuration attitude sensor to get accurate attitude from body measurements and known reference observations for spacecraft, moon-sun attitude sensor gets more and more attention for spacecraft accurate attitude determination. But for full moon image situation, the symmetry axis estimation method does not work in moon-sun attitude sensor. A bacterial foraging optimisation-based Scale Invariant Feature Transform (SIFT) algorithm is proposed to recognise the Crisium Sea in moon image quickly for direction estimation in moon-sun attitude sensor. Inspired by the foraging behaviour of bacteria, the bacterial foraging algorithm-based optimisation is applied to SIFT for searching the Crisium Sea characters in the full illuminated moon with a developed object function. The experimental results show that the proposed method is more efficient in the direction estimation than that traditional SIFT for the full moon image situation of moon-sun attitude sensor.

Keywords: bacterial foraging optimisation; BFO; moon-sun attitude sensors; SIFT; scale invariant feature transform; spacecraft attitude determination; direction estimation; full moon image.

DOI: 10.1504/IJWMC.2015.068633

International Journal of Wireless and Mobile Computing, 2015 Vol.8 No.2, pp.200 - 205

Received: 22 Jul 2014
Accepted: 28 Aug 2014

Published online: 28 Mar 2015 *

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