Image Perspective Invariant Features Algorithm Based on Particle Swarm Optimization

Journal of Multimedia

关键词: Particle Encoding;    Discrete Set;    Sampling;    Fitness Function;   

Others  :  1017252
DOI  :  10.4304/jmm.9.3.386-393

【 摘 要 】

To solve the problems like affine sampling strategy and sampling point discrete settings etc. of traditional image matching techniques, this paper proposes the image perspective invariant features algorithm based on particle swarm optimization. The algorithm uses the features of the perspective transforming sampling methods to extract the algorithm and uses perspective transforming sampling to simulate scenery. Particle swarm algorithm is used as the optimization tool to optimize the parameters of the sampling, which aims at searching the optimal transformation model between images in continuous rotation parameter space. Experimental results show that the proposed algorithm can get more correctly matched points, search the better transformation model and reasonably reflect the correspondence between the matching images

【 授权许可】

   
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