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Building shadow detection based on multi-thresholding segmentation

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Abstract

The human eye can easily identify shadows of illuminated objects. However, automatically detecting such shadows with the use of computer tools is a challenging research problem. In this paper, an approach toward successful building shadow detection based on multi-threshold image segmentation technique is introduced and analyzed. Accuracy assessment and computing time analyses conducted over seven study areas from two reference datasets show the high performance of our proposed approach in detecting real shadows with a 93.75% accuracy.

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Funding

This study has been funded with support from the National Council for Scientific Research in Lebanon.

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Authors and Affiliations

  1. National Council for Scientific Research, CNRS, 59, Zahia Salmane Street, Jnah, P.O. Box 11-8281, Beirut, Lebanon

    Ali J. Ghandour

  2. Department of Computer and Communication Engineering, Islamic University of Lebanon, P.O. Box 30014, Beirut, Lebanon

    Abedelkarim A. Jezzini

Authors
  1. Ali J. Ghandour
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  2. Abedelkarim A. Jezzini
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Correspondence to Ali J. Ghandour.

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Ghandour, A.J., Jezzini, A.A. Building shadow detection based on multi-thresholding segmentation. SIViP 13, 349–357 (2019). https://doi.org/10.1007/s11760-018-1363-0

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  • DOI: https://doi.org/10.1007/s11760-018-1363-0

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