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Affine SIFT Based on Particle Swarm Optimization

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Fuzzy Information & Engineering and Operations Research & Management

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 211))

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Abstract

As for ASIFT, ASIFT has been proven to be invariant to image scaling and rotation. Specially, ASIFT enables matching of images with severe view point change and outperforms significantly the state-of-the-art methods. It accomplished this by simulating several views of the original images. However, we found that the simulated parameters are continuous, namely, transformations acquired by ASIFT cant express the real relationship between reference and input images. Therefore, a particle swarm optimization based sample strategy is presented in this paper. The basic idea is to search the best transform in continuous parameter space. Experimental results show that the proposed PSO-ASIFT algorithm could get more matches compared with the original ASIFT and SIFT.

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Acknowledgments

The work was supported by Natural Science Foundation of Fujian Province of China (No.2011J01013), and Special Fund of Science, Technology of Fujian Provincial University of China (JK2010013) and Fund of Science, Technology of Xiamen (No. 3502Z20123022). Corresponding author: Professor Shui-li Chen

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Authors and Affiliations

  1. College of Mathematical and Computer Science, Fuzhou University, Fuzhou , 350002, China

    Xue-lian Cao

  2. College of Science, Jimei University, Xiamen , 361021, China

    Guo-Rong Cai

  3. College of Science, Jimei University, Xiamen , 361021, China

    Shui-li Chen

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  1. Xue-lian Cao
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  2. Guo-Rong Cai
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  3. Shui-li Chen
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Correspondence to Shui-li Chen .

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Editors and Affiliations

  1. School of Mathematics and Information Science, Guangzhou University Higher Education Mega Center, Guangzhou, People's Republic of China

    Bing-Yuan Cao

  2. Department of Mathematics and Computer Sciences, Mazandaran University, Babolsar, Iran

    Hadi Nasseri

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Cao, Xl., Cai, GR., Chen, Sl. (2014). Affine SIFT Based on Particle Swarm Optimization. In: Cao, BY., Nasseri, H. (eds) Fuzzy Information & Engineering and Operations Research & Management. Advances in Intelligent Systems and Computing, vol 211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38667-1_7

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  • DOI: https://doi.org/10.1007/978-3-642-38667-1_7

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