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Automatic Hand Detection in Color Images based on skin region verification

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Abstract

Among the modern means of communications that appeared recently, there is the natural computer interaction using hands. Several methods have been proposed for their detection in the literature, and the common methods are based on skin color. The majority of these methods perform on images containing the hand region only or on images containing the hand and the forearm regions, but few of them have been interested to deal automatically for both situations.

In this paper, we propose a new method of automatic hand detection in color images based on skin region verification. Using the 2D properties of hand components (fingertips, hand palm, wrist) we verify if the skin region treated contains the hand region with or without the presence of the forearm, and for each situation the hand is detected differently. Compared to other methods of literature, our method avoids several scenarios of misdetection and process in a consistent manner through the verification and detection stages. Using a database containing 899 color images of hand gestures, we evaluated the efficiency of our method and we compared it to other methods of literature, the results obtained were very satisfactory.

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Notes

  1. http://sun.aei.polsl.pl/~mkawulok/gestures/

  2. https://drive.google.com/open?id=0B-3ecN-Ys2rod2lYRE45WHdTWkk

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Authors and Affiliations

  1. University of Badji Mokhtar, Annaba, Algeria

    Sofiane Medjram & Yamina Mohamed Ben Ali

  2. University of Mohamed Khider, Biskra, Algeria

    Mohamed Chaouki Babahenini

  3. University of Valenciennes, Famars, France

    Abdelmalik Taleb-Ahmed

Authors
  1. Sofiane Medjram
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  2. Mohamed Chaouki Babahenini
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  3. Abdelmalik Taleb-Ahmed
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  4. Yamina Mohamed Ben Ali
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Correspondence to Sofiane Medjram.

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Medjram, S., Babahenini, M.C., Taleb-Ahmed, A. et al. Automatic Hand Detection in Color Images based on skin region verification. Multimed Tools Appl 77, 13821–13851 (2018). https://doi.org/10.1007/s11042-017-4995-0

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  • DOI: https://doi.org/10.1007/s11042-017-4995-0

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