A hybrid genetic algorithm and bacterial foraging approach for global optimization
Information Sciences: an International Journal
Adaptive computational chemotaxis in bacterial foraging optimization: an analysis
IEEE Transactions on Evolutionary Computation
Automatic circle detection on digital images with an adaptive bacterial foraging algorithm
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Scheduling optimisation for supply chain in networked manufacturing
International Journal of Computer Applications in Technology
Modified bacterial foraging algorithm based multilevel thresholding for image segmentation
Engineering Applications of Artificial Intelligence
A novel bacterial foraging technique for edge detection
Pattern Recognition Letters
Identification for fractional order rational models based on particle swarm optimisation
International Journal of Computer Applications in Technology
SINS/CNS integrated navigation solution using adaptive unscented Kalman filtering
International Journal of Computer Applications in Technology
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Accurate vehicle attitude is critical for spacecraft in the navigation and control applications. Moon-sun attitude sensor is a stand alone configuration attitude sensor to get accurate attitude from body measurements and known reference observations. Inspired by the foraging behaviour of bacteria, the bacterial foraging algorithm reaches global minima by employing chemotaxis, swarming, reproduction and elimination and dispersal events. In this paper, we developed a bacterial foraging optimisation based symmetry axis estimation method from observed moon image for moon-sun attitude sensor. After the pre-processing of the source image which includes filtering and segmentation steps, bacterial foraging is applied to the segmented image for searching symmetry axis of the illuminated moon with a developed object function. The offset distance and rotation angle are used as optimisation parameters for symmetry axis estimation. The experimental results show that the proposed method is efficient for the symmetry axis estimation of moon image.