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Hybrid Shadow Restitution Technique for Shadow-Free Scene Reconstruction

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Advances in Signal Processing and Intelligent Recognition Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 264))

Abstract

Shadows are treated as a noise in computer vision scenario, even though it may found useful in many applications.  This research focuses the insignificant shadow restitution methodology to improve the scene visibility and to support the dynamic range reduction. The Hybrid technique combines the physical, geometric, textural, spatial and photometric features for shadow detection. Using feature importance statistics the appropriate criteria is chosen and applied. The experiments over wide dataset prove that the proposed hybrid technique outperforms peer research proposals with the expense of computational cost and time. The output results in a shadow-free, visually plausible high quality image.

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Author information

Authors and Affiliations

  1. Dept of CSE, NIT, Puducherry, India

    Muthukumar Subramanyam

  2. CITE, MS University, Tirunelveli, India

    Krishnan Nallaperumal, Pasupathi Perumalsamy, Shashikala Durairaj, S. Selva Kumar & S. Gayathri Devi

  3. Dept of CSE, Pondicherry University, Pondicherry, India

    Ravi Subban

Authors
  1. Muthukumar Subramanyam
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  2. Krishnan Nallaperumal
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  3. Ravi Subban
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  4. Pasupathi Perumalsamy
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  5. Shashikala Durairaj
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  6. S. Selva Kumar
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  7. S. Gayathri Devi
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Corresponding author

Correspondence to Muthukumar Subramanyam .

Editor information

Editors and Affiliations

  1. Technopark Campus, Indian Institute of Information Technology and Management – Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  2. Center for Computing Research, National Polytechnic Institute, Mexico City, Mexico

    Alexander Gelbukh

  3. Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, India

    Jayanta Mukhopadhyay

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Subramanyam, M. et al. (2014). Hybrid Shadow Restitution Technique for Shadow-Free Scene Reconstruction. In: Thampi, S., Gelbukh, A., Mukhopadhyay, J. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-319-04960-1_45

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  • DOI: https://doi.org/10.1007/978-3-319-04960-1_45

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04959-5

  • Online ISBN: 978-3-319-04960-1

  • eBook Packages: EngineeringEngineering (R0)

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