Improving the Method of Wrist Localization Local Minimum-Based for Hand Detection

  • Sofiane Medjram
  • Mohamed Chaouki Babahenini
  • Mohamed Ben Ali Yamina
  • Abdelmalik Taleb-AhmedEmail author
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 1)


Nowadays, hand detection and gestures recognition have become very popular in human computer interaction systems. Several methods of hand detection based on wrist localization have been proposed but the majority work only with short sleeves and they are not efficient in front of all the challenges. Hand detection based on wrist localization proposed by Grzejszczak et al. (Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013 439–449, 2013), Nelpa et al. (Man Mach Interact 3(242):123–130, 2014) [3, 4] use the property of local minima along the contour of the skin mask obtained in the first stage to detect the wrist position. Although this technique provides good results where the skin mask contains the hand and the forearm, it still sensitive to the short contour where the skin mask contains the hand region only which generate false detection of the hand. We present in this paper an assessment of this method where the skin mask contains the hand region only. The main idea is based on the 2D shape properties of the hand and its components. Using 134 color images with their ground- truth, we evaluated the method enhanced and the results obtained were very satisfactory compared to the original one.


Hand detection Wrist localization Skin detection Gestures recognition 


  1. 1.
    Paulson, B., Cummings, D., Hammond, T.: Object interaction detection using hand posture cues in an office setting. Int. J. Hum. Comput. Stud. 69, 19–29 (2011)CrossRefGoogle Scholar
  2. 2.
    Wang, R.Y., Popović, J.: Real-time hand-tracking with a color glove. ACM Trans. Graph. 28, 1 (2009)Google Scholar
  3. 3.
    Grzejszczak, T., Nalepa, J., Kawulok, M.: Real-time wrist localization in hand silhouettes. In: Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013, pp. 439–449 (2013)Google Scholar
  4. 4.
    Nelpa, J., Grzejszczak, T., Kawulok, M.: Wrist localization in color images for hand gesture recognition. Man Mach. Interact. 3(242), 123–130 (2014)Google Scholar
  5. 5.
    Yeo, H.S., Lee, B.G., Lim, H.: Hand tracking and gesture recognition system for human-computer interaction using low-cost hardware. Multimed. Tools Appl. 1–29 (2013)Google Scholar
  6. 6.
    Toni, B., Darko, J., IPRO: A robust hand detection and tracking algorithm with application to natural user interface (2012)Google Scholar
  7. 7.
    Xie, S., Pan, J.: Hand detection using robust color correction and gaussian mixture model. In: 2011 Sixth International Conference on Image and Graphics, pp. 553–557. IEEE (2011)Google Scholar
  8. 8.
    Choi, J., Seo, B.: Robust hand detection for augmented reality interface. In: Proceedings of the 8th International Conference on Virtual Reality Continuum and its Applications in Industry, pp. 319–322 (2009)Google Scholar
  9. 9.
    Vidya, K., Deryl, R., Dinesh, K., Rajabommannan, S., Sujitha, G.: Enhancing hand interaction patterns for virtual objects in mobile augmented reality using marker-less tracking. In: 2014 International Conference on Computing for Sustainable Global Development, INDIACom 2014, pp. 705–709 (2014)Google Scholar
  10. 10.
    Grzejszczak, T., Kawulok, M., Galuszka, A.: Hand landmarks detection and localization in color images. Multimed. Tools Appl. (2015)Google Scholar
  11. 11.
    Mittal, A., Zisserman, A., Torr, P.: Hand detection using multiple proposals. Proc. Br. Mach. Vis. Conf. 75, 1–75.11 (2011)Google Scholar
  12. 12.
    Kerdvibulvech, C.: A methodology for hand and finger motion analysis using adaptive probabilistic models. EURASIP J. Embed. Syst. 2014, 18 (2014)CrossRefGoogle Scholar
  13. 13.
    Stergiopoulou, E., Papamarkos, N.Ã.: Engineering applications of artificial intelligence hand gesture recognition using a neural network shape fitting technique. Eng. Appl. Artif. Intell. 22, 1141–1158 (2009)CrossRefGoogle Scholar
  14. 14.
    Mao, G.-Z., Wu, Y.-L., Hor, M.-K., Tang, C.-Y.: Real-time hand detection and tracking against complex background. In: 2009 Fifth International Conference Intelligent Information Hiding and Multimedia Signal Processing, pp. 905–908 (2009)Google Scholar
  15. 15.
    Licsar, A., Sziranyi, T.: Hand gesture recognition in camera-projector system. Lect. Notes Comput. Sci. 83–93 (2004)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Sofiane Medjram
    • 1
  • Mohamed Chaouki Babahenini
    • 2
  • Mohamed Ben Ali Yamina
    • 1
  • Abdelmalik Taleb-Ahmed
    • 3
    Email author
  1. 1.University of Badji Mokhtar AnnabaAnnabaAlgeria
  2. 2.University of Mohamed Khider BiskraBiskraAlgeria
  3. 3.University of ValenciennesValenciennesFrance

Personalised recommendations