Research of Image Registration Based on Maximum Entropy Template Selection Algorithm

Abstract:

This paper concerns an improved adaptive genetic algorithm, and the method is applied to the Maximum Entropy Template Selection Algorithm image registration. This method includes adjusting the probability of crossover and mutation in the evolutionary process. The method can overcome the disadvantage of traditional genetic algorithm that is easy to get into a local optimum answer. Results show our method is insensitive to the ordering, rotation and scale of the input images so it can be used in image stitching and retrieval of images & videos.

• Periodical: Advanced Materials Research (Volumes 268-270)
• Pages: 1138-1143
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.268-270.1138
• Online since: July 2011
• Authors: Hong Ying Qin
• Keywords: Crossover, Genetic Algorithm (GA), Image Registration, Mutation

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