Image Matching Based on Bacterial Foraging Algorithm
To increase the speed of image matching, this paper combines Bacterial Foraging Algorithm (BFA) of swarm intelligence with wavelet transform, and presents a fast matching method. The method regards the problem of image matching as a search for the optimal solution. To provide artificial bacterial swarm algorithm with an appropriate fitness function, the Normalized Product correlation (NPROD) is employed to measure the similarity between the template image and the searching image. Then the best coarse matching position is gradually approaching by chemotaxis, elimination and dispersal, and reproduction behaviors of artificial bacterial. Finally, the best matching position is found out according to the coarse matching position. Experimental results show that the proposed method is fast and efficient.
Riza Esa and Yanwen Wu
H. P. Tian "Image Matching Based on Bacterial Foraging Algorithm", Advanced Materials Research, Vols. 301-303, pp. 859-863, 2011