Visual Recognition of Bengali Sign Language using Local Binary Pattern Compared with ANN

Authors

  • Md. Abdur Rahim

Keywords:

sign language, ANN, back propagation algorithm, local binary pattern

Abstract

This paper presents an overview of visual recognition of Bengali Sign Language. In this paper we learn and detect a sequence of sign words and recognize the sign language that are understandable to the deaf and hearing impaired people to help normal people understand the meaning of these words. The research discusses the characteristics of the human sign languages, the requirements and difficulties behind visual sign recognition, how to deal with others persons and the different techniques used in the sign language recognition. The paper consists of two major parts, namely the learning part and the detection part. The system takes the sign images as its input. First sign images are learnt by the proposed system. When a sign image is given for recognition, the detection part identifies the image with the help of previously learned images. For learning and detection we have used local binary pattern compared with back propagation algorithm of Artificial Neural Network. We believe that this research will be of much help to express their thoughts and feelings between the deaf people and the normal people.

How to Cite

Md. Abdur Rahim. (2014). Visual Recognition of Bengali Sign Language using Local Binary Pattern Compared with ANN. Global Journal of Computer Science and Technology, 14(F2), 1–6. Retrieved from https://computerresearch.org/index.php/computer/article/view/88

Visual Recognition of Bengali Sign Language using Local Binary Pattern Compared with ANN

Published

2014-03-15