TITLE:
Hand Gesture Recognition Approach for ASL Language Using Hand Extraction Algorithm
AUTHORS:
Alhussain Akoum, Nour Al Mawla
KEYWORDS:
Hand Gesture, American Sign Language, Gesture Analysis, Edge Detection, Correlation, Background Modeling
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.8 No.8,
August
28,
2015
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.