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Genetic and Evolutionary Computing pp 269–275Cite as

Segmentation of Video Image Using Changing Detection and Block Based Approach

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 387))

Abstract

Segmentation of object from video image sequence is very important in many aspects of multimedia application. We present an approach to discover and segment foreground object(s) in video. Our approach is to identify 8x8 blocks in any frame and compute a series of binary partitions among those blocks and compare each frame of blocks finding change of all frames in images. Our approach is automatically segmentation of object on the persistent foreground regions of interest. We apply our method to challenge standard videos, and show competitive or better results than the state-of-the-art.

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Author information

Authors and Affiliations

  1. University of Computer Studies, Mandalay, Myanmar

    Mie Mie Tin

  2. Myanmar Institute of Information Technology, Mandalay, Myanmar

    Mie Mie Khin

Authors
  1. Mie Mie Tin
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  2. Mie Mie Khin
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Corresponding author

Correspondence to Mie Mie Khin .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Thi Thi Zin

  2. School of Computer Science and Tech..., Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China

    Jerry Chun-Wei Lin

  3. College of Information Science and Engg, Fujian University of Technology, Fuzhou, China

    Jeng-Shyang Pan

  4. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Pyke Tin

  5. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Mitsuhiro Yokota

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© 2016 Springer International Publishing Switzerland

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Tin, M.M., Khin, M.M. (2016). Segmentation of Video Image Using Changing Detection and Block Based Approach. In: Zin, T., Lin, JW., Pan, JS., Tin, P., Yokota, M. (eds) Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol 387. Springer, Cham. https://doi.org/10.1007/978-3-319-23204-1_27

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  • DOI: https://doi.org/10.1007/978-3-319-23204-1_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23203-4

  • Online ISBN: 978-3-319-23204-1

  • eBook Packages: EngineeringEngineering (R0)

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