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A Simple and Mighty Arrowhead Detection Technique of Bangla Sign Language Characters with CNN

  • Md. Sanzidul IslamEmail author
  • Sadia Sultana Sharmin Mousumi
  • AKM Shahariar Azad Rabby
  • Syed Akhter Hossain
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1035)

Abstract

Sign Language is argued as the first Language for hearing impaired people. It is the most physical and obvious way for the deaf and dumb people who have speech and hearing problems to convey themselves and general people. So, an interpreter is wanted whereas a general people needs to communicate with a deaf and dumb person. In respect to Bangladesh, 2.4 million people uses sign language but the works are extremely few for Bangladeshi Sign Language (BdSL). In this paper, we attempt to represent a BdSL recognition model which are constructed using of 50 sets of hand sign images. Bangla Sign alphabets are identified by resolving its shape and assimilating its structures that abstract each sign. In proposed model, we used multi-layered Convolutional Neural Network (CNN). CNNs are able to automate the method of structure formulation. Finally the model gained 92% accuracy on our dataset.

Keywords

Bangla Sign Language NLP Computer vision Machine learning Image processing Sign language characters BdSL BSL CNN Pattern recognition 

Notes

Acknowledgement

I would like to express my heartiest appreciation to all those who provided us the possibility to complete this research under the Daffodil International University. A special gratitude we give to Daffodil International University NLP and Machine Learning Research LAB for their instructions and support. Furthermore, I would also like to acknowledge that, this research partially supported by Bijaynagar Deaf School, Mirpur Deaf School, Mymensing Deaf School, CDD (Centre for Disability in Development) and all of the volunteers team who gave permission to collect valuable data. Any errors are our own and should not tarnish the reputations of these esteemed persons.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Md. Sanzidul Islam
    • 1
    Email author
  • Sadia Sultana Sharmin Mousumi
    • 1
  • AKM Shahariar Azad Rabby
    • 1
  • Syed Akhter Hossain
    • 1
  1. 1.Department of Computer Science and EngineeringDaffodil International UniversityDhakaBangladesh

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