Abstract
Sign language is the language of gestures and postures used for non-verbal communication. This paper presents a novel vision based approach for the detection of isolated signs of Pakistan Sign Language (PSL). The signs representing alphabets of Urdu (national language of Pakistan) are recognized by distinguishing fingers. The algorithm, following a model of seven phases, identifies each of the five fingers from their respective positions. After fingers’ recognition, signs are deduced from their states of being raised or down. For quick recognition, signs are categorized into three groups based on the thumb position. Five testers evaluated the system using a simple low cost USB camera in a semi-controlled environment. The results obtained are encouraging as accuracy of the system exceeds a level of 85.4%.
Mohammad Raees, Sehat Ullah. (2014) Alphabet Signs Recognition using Pixels-based Analysis, Conference on Language and Technology 2014.
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Publisher
Center for Language Engineering
Country
Pakistan
City
Karachi
From
13-11-2014
To
15-11-2014