EMCC: Enhancement of Motion Chain Code for Arabic Sign Language Recognition

Abstract

In this paper, an algorithm for Arabic sign language recognition is proposed. The proposed algorithm facilitates the communication between deaf and non-deaf people. A possible way to achieve this goal is to enable computer systems to visually recognize hand gestures from images. In this context, a proposed criterion which is called Enhancement Motion Chain Code (EMCC) that uses Hidden Markov Model (HMM) on word level for Arabic sign language recognition (ArSLR) is introduced. This paper focuses on recognizing Arabic sign language at word level used by the community of deaf people. Experiments on real-world datasets showed that the reliability and suitability of the proposed algorithm for Arabic sign language recognition. The experiment results introduce the gesture recognition error rate for a different sign is 1.2% compared to that of the competitive method.

Authors and Affiliations

Mahmoud Abdo, Alaa Hamdy, Sameh Salem, Elsayed Saad

Keywords

Related Articles

Generating a Highlight Moments Summary Video of Apolitical Event using Ontological Analysis on Social Media Speech Sentiment

Numerous viewers choose to watch political or presidential debates highlights via TV or internet, rather than seeing the whole debate nowadays, which requires a lot of time. However, the task of making a debate summary,...

Video Streaming Analytics for Traffic Monitoring Systems

It is considered a difficult task to have check on traffic during rush hours. Traditional applications are man-ual, costly, time consuming, and the human factors involved. Large scale data is being generated from differe...

A New Parallel Matrix Multiplication Algorithm on Tree-Hypercube Network using Iman1 Supercomputer

The tree-hypercube (TH) interconnection network is relatively a new interconnection network, which is constructed from tree and hypercube topologies. TH is developed to support parallel algorithms for solving computation...

A Comprehensive Comparative Analysis of Two Novel Underwater Routing Protocols

The most unmanned area of this planet is sheltered with water; that is roughly 71.9% of the total area of this planet. A large quantity of marine life is present in this area. That is the reason underwater research is bo...

An Efficient Algorithm for Resource Allocation in Parallel and Distributed Computing Systems

Resource allocation in heterogeneous parallel and distributed computing systems is the process of allocating user tasks to processing elements for execution such that some performance objective is optimized. In this pape...

Download PDF file
  • EP ID EP90418
  • DOI 10.14569/IJACSA.2015.061215
  • Views 133
  • Downloads 0

How To Cite

Mahmoud Abdo, Alaa Hamdy, Sameh Salem, Elsayed Saad (2015). EMCC: Enhancement of Motion Chain Code for Arabic Sign Language Recognition. International Journal of Advanced Computer Science & Applications, 6(12), 109-117. https://europub.co.uk/articles/-A-90418