Hand Gesture Recognition Approach for ASL Language Using Hand Extraction Algorithm

Nour Al  Mawla; Alhussain  Akoum

doi:10.4236/jsea.2015.88041

Alhussain Akoum, Nour Al Mawla

Abstract: In a general overview, signed language is a technique used for communicational purposes by deaf people. It is a three-dimensional language that relies on visual gestures and moving hand signs that classify letters and words. Gesture recognition has been always a relatively fearful subject that is adherent to the individual on both academic and demonstrative levels. The core objective of this system is to produce a method which can identify detailed humanoid nods and use them to either deliver ones thoughts and feelings, or for device control. This system will stand as an effective replacement for speech, enhancing the individual’s ability to express and intermingle in society. In this paper, we will discuss the different steps used to input, recognize and analyze the hand gestures, transforming them to both written words and audible speech. Each step is an independent algorithm that has its unique variables and conditions.

Keywords: Hand Gesture, American Sign Language, Gesture Analysis, Edge Detection, Correlation, Background Modeling

Cite this paper: Akoum, A. and Mawla, N. (2015) Hand Gesture Recognition Approach for ASL Language Using Hand Extraction Algorithm. Journal of Software Engineering and Applications, 8, 419-430. doi: 10.4236/jsea.2015.88041.

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