Title: Bacterial foraging-based SIFT for full moon image direction estimation
Authors: Liyong Ma; Yong Zhang
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.
Int. J. of Wireless and Mobile Computing, 2015 Vol.8, No.2, pp.200 - 205
Submission date: 15 Jul 2014
Date of acceptance: 28 Aug 2014
Available online: 28 Mar 2015