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An Improved RANSAC Image Stitching Algorithm Based Similarity Degree

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Book cover MultiMedia Modeling (MMM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9517))

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Abstract

In terms of the deficiency in the aspects that the higher computational complexity caused by excessive iterations and the easy happened stitching dislocation caused by the difficult-to-determine parameters. In this paper, an improved RANSANC algorithm based similarity degree is proposed and is applied in image mosaic. This improved algorithm includes that sorting rough matched points by similarity degree, calculating transformation matrix, rejecting obviously wrong matched points and executing classical RANSAC algorithm. It is demonstrated by the experiments that this algorithm can effectively remove wrong matched pairs, reduce iteration times and shorten the calculation time, meanwhile ensure the accuracy of requested matrix transformation. By this method can get high quality stitching images.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

    Yule Ge & Chunxiao Gao

  2. North Automatic Control Technology Institute, Taiyuan, Shanxi, China

    GuoDong Liu

Authors
  1. Yule Ge
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  2. Chunxiao Gao
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  3. GuoDong Liu
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Corresponding author

Correspondence to Yule Ge .

Editor information

Editors and Affiliations

  1. University of Texas at San Antonio, San Antonio, USA

    Qi Tian

  2. Dept. of Information Engineering, University of Trento, Povo, Trento, Italy

    Nicu Sebe

  3. EECS, University of Central Florida, Orlando, Florida, USA

    Guo-Jun Qi

  4. EURECOM, Sophia-Antipolis, France

    Benoit Huet

  5. Hefei University of Technology, Hefei, Anhui, China

    Richang Hong

  6. School of Computing and Information, Hefei University of Technology, Hefei, Anhui, China

    Xueliang Liu

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© 2016 Springer International Publishing Switzerland

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Ge, Y., Gao, C., Liu, G. (2016). An Improved RANSAC Image Stitching Algorithm Based Similarity Degree. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9517. Springer, Cham. https://doi.org/10.1007/978-3-319-27674-8_17

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  • DOI: https://doi.org/10.1007/978-3-319-27674-8_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27673-1

  • Online ISBN: 978-3-319-27674-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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