Kurdish Sign Language Recognition System

Authors

  • Abdulla D. Hashim Department of Computer Science and Engineering, University of Kurdistan Hewler, Erbil, Kurdistan Region – F.R. Iraq
  • Fattah Alizadeh Department of Computer Science and Engineering, University of Kurdistan Hewler, Erbil, Kurdistan Region – F.R. Iraq http://orcid.org/0000-0002-0690-1147

DOI:

https://doi.org/10.25079/ukhjse.v2n1y2018.pp1-6

Keywords:

Image Processing, Kurdish, Machine Learning, Sign Language

Abstract

Deaf people all around the world face difficulty to communicate with the others. Hence, they use their own language to communicate with each other. On the other hand, it is difficult for deaf people to get used to technological services such as websites, television, mobile applications, and so on. This project aims to design a prototype system for deaf people to help them to communicate with other people and computers without relying on human interpreters. The proposed system is for letter-based Kurdish Sign Language (KuSL) which has not been introduced before. The system would be a real-time system that takes actions immediately after detecting hand gestures. Three algorithms for detecting KuSL have been implemented and tested, two of them are well-known methods that have been implemented and tested by other researchers, and the third one has been introduced in this paper for the 1st time. The new algorithm is named Gridbased gesture descriptor. It turned out to be the best method for the recognition of Kurdish hand signs. Furthermore, the result of the algorithm was 67% accuracy of detecting hand gestures. Finally, the other well-known algorithms are named scale invariant feature transform and speeded-up robust features, and they responded with 42% of accuracy.

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Author Biographies

  • Abdulla D. Hashim, Department of Computer Science and Engineering, University of Kurdistan Hewler, Erbil, Kurdistan Region – F.R. Iraq

    Abdullah Dlshad Hashim, was born in Erbil in 1992. He has received his B.Sc. degree from the department of Computer Science and Engineering of the University of Kurdistan Hewler in 2017. His research interests mainly comprises Image processing, Software Development and Evaluation.   

  • Fattah Alizadeh, Department of Computer Science and Engineering, University of Kurdistan Hewler, Erbil, Kurdistan Region – F.R. Iraq

    Fattah Alizadeh is Assistant Professor in Computer Science at the School of Computer Science and Engineering, University of Kurdistan Hewler (Kurdistan region, Iraq). He holds a Ph.D. degree in Computer Image Processing from the university of Dublin City University (Ireland), a Master-Degree in Computer Software Engineering from Iran University of Science and Technology, Tehran (Iran) and a Bachelor of Science from Shiraz University, Shiraz (Iran) in Computer System Engineering. His research interests include: Machine Vision, 3D Model Search, Retrieval and Segmentation, Machine Learning. 

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Published

2018-06-30

Issue

Section

Research Articles

How to Cite

Kurdish Sign Language Recognition System. (2018). UKH Journal of Science and Engineering, 2(1), 1-6. https://doi.org/10.25079/ukhjse.v2n1y2018.pp1-6