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Basic Investigation into Hand Shape Recognition Using Colored Gloves Taking Account of the Peripheral Environment

  • Takahiro Sugaya
  • Takayuki Suzuki
  • Hiromitsu Nishimura
  • Hiroshi Tanaka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8016)

Abstract

Although infrared cameras are sometimes used for posture and hand shape recognition, they are not used widely. In contrast, visible light cameras are widely used as web cameras and are implemented in mobile and smart phones. We have used color gloves in order to allow hand shapes to be recognized by visible light cameras, which expands both the type of background that can be used and the application areas. It is considered that the hand shape recognition using color gloves can be used to express many patterns and can be used for many applications such as communication and input interfaces, etc. The recognition performance depends on the color information of the color gloves, which is affected by the environment, especially the illumination conditions, that is bright or dim lighting. Hue values are used to detect color in this investigation. The relative finger positions and finger length are used to confirm the validity of color detection. We propose a method of rejecting image frames that includes a color detection error, which will, in turn, give rise to a hand shape recognition error. Experiments were carried out under three different illumination conditions. The effectiveness of the proposed method has been verified by comparing the recognition success ratio of the conventional method and with the results using the proposed methods.

Keywords

Colored Gloves Visible Light Camera Color Detection Hue Value Peripheral Environment 

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References

  1. 1.
    Khan, Z.R., Ibraheem, A.N.: Comparative Study of Hand Gesture Recognition System. In: Proc. of International Conference of Advanced Computer Science & Information Technology in Computer Science & Information Technology (CS & IT), vol. 2(3), pp. 203–213 (2012)Google Scholar
  2. 2.
    Baatar, B., Tanaka, J.: Comparing Sensor Based Techniques for Dynamic Gesture Recognition. In: The 10th Asia Pacific Conference on Computer Human Interaction, APCHI 2012, Poster 2P-21 (2012)Google Scholar
  3. 3.
    Matsuda, Y., Sakuma, I., Jimbo, Y., Kobayashi, E., Arafune, T., Isomura, T.: Development of Finger Braille Recognition System. Journal of Biometrical Science and Engineering 5(1), 54–65 (2010)CrossRefGoogle Scholar
  4. 4.
    Jing, L., Zhou, Y., Cheng, Z., Wang, J.: A Recognition Method for One-stroke Finger Gestures Using a MEMS 3D Accelerometer. IEICE Transactions on Information and Systems E94-D(5), 1062–1072 (2011)CrossRefGoogle Scholar
  5. 5.
    Yoruk, E., Konukoglu, E., Sankur, B., Darbon, J.: Shape - Based Hand Recognition. IEEE Transactions on Image Processing 15(7), 1803–1815 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Takahiro Sugaya
    • 1
  • Takayuki Suzuki
    • 1
  • Hiromitsu Nishimura
    • 1
  • Hiroshi Tanaka
    • 1
  1. 1.Kanagawa Institute of TechnologyAtsugi-shiJapan

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