Paper Title:
Image Matching Based on Bacterial Foraging Algorithm
  Abstract

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.

  Info
Periodical
Advanced Materials Research (Volumes 301-303)
Chapter
Chapter 2: Measuring and Testing Techniques
Edited by
Riza Esa and Yanwen Wu
Pages
859-863
DOI
10.4028/www.scientific.net/AMR.301-303.859
Citation
H. P. Tian, "Image Matching Based on Bacterial Foraging Algorithm", Advanced Materials Research, Vols. 301-303, pp. 859-863, 2011
Online since
July 2011
Authors
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Price
$32.00
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