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Journal of Emerging Trends in Computing and Information Sciences >> Call for Papers Vol. 8 No. 3, March 2017

Journal of Emerging Trends in Computing and Information Sciences

Development of a new Arabic Sign Language Recognition Using K-Nearest Neighbor Algorithm

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Author Prof. Reyadh Naoum, Dr.Hussein H. Owaied, Shaimaa Joudeh
ISSN 2079-8407
On Pages 1173-1178
Volume No. 3
Issue No. 8
Issue Date August 01, 2012
Publishing Date August 01, 2012
Keywords Arabic Sign Language, Artificial Neural Network, Image Processing, OCR, Sign Language Processing, Text-based Image Processing.


Abstract

This paper presents a new Arabic sign language recognition using K-nearest Neighbor algorithm. The algorithm is designed to work as a first level detection upon a series of steps to bring the captured character images into actual spelling. The algorithm acts in a high performance execution which is exactly needed for such type of systems. K-Nearest Neighbor Algorithm and feature extraction are the guidelines of the recognition system, because hand gestures is treated as a block of curves needed to be extracted in the best fit with a predefined character set in the knowledge base. The specific image preprocessing to form a new idea of histogram and a histogram transition table is formed as a hashed string of transformation of block histogram sequence using K-Nearest Neighbor Algorithm. Preparing the knowledge base as a sequence of characters for one time and will and fast easily compared to detecting the character input.  

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