International Journal of Advance Computational Engineering and Networking (IJACEN)
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Statistics report
Aug. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 88
Paper Published : 1238
No. of Authors : 3111
  Journal Paper

Paper Title
Hand Detection For Sign Language Recognition Applying Hidden Markov Model

Abstract
The study of developing interface with computers using gestures of human body such as hand movements keeps growing in interest. This is to provide more natural, innovative and sophisticated way of non-verbal communication, such as sign language, in human computer interaction. A review on this hand gesture detection and recognition based on computer vision technique remains a very challenging task. Nevertheless, this paper explores hand detection and hand gesture recognition. The hand detection uses skin color spaces such as HSV and YCrCb are applied. However, there are limitations that are needed to be considered. Almost all of skin color space models are sensitive to quickly changing or mixed lighting circumstances. The Hidden Markov Model (HMM) is proposed to be implemented in hand recognition for alphabetical sign language. There are certain restrictions in order for the hand recognition to give better results such as the distance of user’s hand to the computer camera and the posture of the hand shown by user. Keywords- Hand Detection, Hand Gesture, Sign Language, Hidden Markov Model.


Author - Mohd Noah A. Rahman, Armanadurni Abdul Rahman, Afzaal H. Seyal, Norhafilah Bara

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| Published on 2016-03-25
   
   
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