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A Survey on Various Shadow Detection and Removal Methods

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Computational Vision and Bio-Inspired Computing ( ICCVBIC 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1108))

Abstract

Shadows plays an inevitable part in an image and also the major source of hindrance in Computer Vision analysis. Shadow detection is the performance enhancement process that increases the accuracy of the Computer Vision algorithms like Object Tracking, Object Recognition, Image Segmentation, Surveillance, Scene Analysis, Stereo, Tracking, etc. Shadows limit the stability of these algorithms, and hence detecting shadows and its elimination are profound pre-processing techniques for improving execution of Vision algorithms efficiently. To label the challenges under various environmental conditions, researches have been carried out to develop various algorithms and techniques for shadow detection. This paper objective is to bring comparative analysis of shadow detection techniques with their pros and cons.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India

    P. C. Nikkil Kumar & P. Malathi

Authors
  1. P. C. Nikkil Kumar
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  2. P. Malathi
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Corresponding author

Correspondence to P. C. Nikkil Kumar .

Editor information

Editors and Affiliations

  1. Department of CSE, RVS Technical Campus, Coimbatore, India

    S. Smys

  2. Faculty of Engineering, Faculdade de Engenharia da Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

  3. Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  4. School of Computing, Tokyo Institute of Technology, Tokyo, Japan

    Abdullah M. Iliyasu

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✓ All authors declare that there is no conflict of interest

✓ No humans/animals involved in this research work.

✓ We have used our own data.

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Nikkil Kumar, P.C., Malathi, P. (2020). A Survey on Various Shadow Detection and Removal Methods. In: Smys, S., Tavares, J., Balas, V., Iliyasu, A. (eds) Computational Vision and Bio-Inspired Computing. ICCVBIC 2019. Advances in Intelligent Systems and Computing, vol 1108. Springer, Cham. https://doi.org/10.1007/978-3-030-37218-7_45

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