• DocumentCode
    3713859
  • Title

    Finger application using K-Curvature method and Kinect sensor in real-time

  • Author

    M. Zabri Abu Bakar;Rosdiyana Samad;Dwi Pebrianti;Mahfuzah Mustafa;Nor Rul Hasma Abdullah

  • Author_Institution
    Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang (UMP), 26600 Pekan, Malaysia
  • fYear
    2015
  • Firstpage
    218
  • Lastpage
    222
  • Abstract
    Gesture is one of the important aspects of human interaction and also in the context of human computer interaction. Gesture recognition is the mathematical interpretation of a human motion by a computing device. It is often used hand gestures for input commands in personal computers. By recognizing the hand gesture as input, it allows the user to access the computer interactively and makes interaction more natural. This paper presents a finger detection application by using Kinect. Kinect is a depth sensor that is an effective device to capture the gesture in real-time. To detect and recognize the fingertips, it needs to extract the detail of the captured hand image using image processing methods. In this paper, the proposed method is to detect and recognize the fingertips by using the K-Curvature algorithm. Finally, the finger counting application is applied and the proposed method is discussed at the end of this paper. The results obtained from the experiment show that the acceptable average accuracy for the fingertips detection is 73.7% and the average processing time is 15.73 ms. By considering this result, the application of the proposed method can be extended to the hand rehabilitation system.
  • Keywords
    "Thumb","Gesture recognition","Image color analysis","Real-time systems","Robot sensing systems","Image segmentation"
  • Publisher
    ieee
  • Conference_Titel
    Technology Management and Emerging Technologies (ISTMET), 2015 International Symposium on
  • Type

    conf

  • DOI
    10.1109/ISTMET.2015.7359032
  • Filename
    7359032