Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Indian Sign Language Recognition System for Deaf and Dumb Using Image Processing and Fingerspelling:A Technical Review


Affiliations
1 BMIIT, India
2 Babu Madhav Institute of Information Technology, Uka Tarsadia University-Bardoli, India
     

   Subscribe/Renew Journal


In deaf and dumb communication, they use sign language to communicate with each other. Communication is the way to convey our thoughts, message or information. Hearing and speech disabled people faces many problems when they communicate with normal people. They uses sign language person, which includes hand gesture, facial expressions, and head movement to convey their message. Using the image processing techniques, it is possible that system will be develop to help those disabled people for effective interaction with normal people. This paper compares and discusses various techniques that are used worldwide for region wise sign languages and proposed an idea that may applicable to develop a communication system for Indian Sign Language. An image processing based system can be made that will work on smartphones and will recognize sign perform by deaf-dumb and generate text or audio output for normal person and vice-versa communication.

Keywords

Sign Language, Deaf and Dumb People, Communication, Image Processing, Smartphones, Hand Gestures.
Subscription Login to verify subscription
User
Notifications
Font Size


  • A. Sood and A. Mishra, “AAWAAZ: A communication system for deaf and dumb,” 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2016.
  • V. Adithya, P. R. Vinod, and U. Gopalakrishnan, “Artificial neural network based method for Indian sign language recognition,” 2013 IEEE Conference on Information and Communication Technologies, 2013.
  • R. Shangeetha., V. Valliammai., and S. Padmavathi., “Computer vision based approach for Indian Sign Language character recognition,” 2012 International Conference on Machine Vision and Image Processing (MVIP), 2012.
  • S. Rathi and U. Gawande, “Development of full duplex intelligent communication system for deaf and dumb people,” 2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence, 2017.
  • “Human–computer interaction,” Wikipedia, 23-Jan-2018. [Online]. Available: https://en.wikipedia.org
  • B. Rajapandian, V. Harini, D. Raksha, and V. Sangeetha, “A novel approach as an AID for blind, deaf and dumb people,” 2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS), 2017.
  • M. S. Nair, A. P. Nimitha, and S. M. Idicula, “Conversion of Malayalam text to Indian sign language using synthetic animation,” 2016 International Conference on Next Generation Intelligent Systems (ICNGIS), 2016.
  • S. Chattoraj, K. Vishwakarma, and T. Paul, “Assistive system for physically disabled people using gesture recognition,” 2017 IEEE 2nd International Conference on Signal and Image Processing (ICSIP), 2017.
  • E. E. Abdallah and E. Fayyoumi, “Assistive Technology for Deaf People Based on Android Platform,” Procedia Computer Science, vol. 94, pp. 295–301, 2016.
  • A. Thalange and S. Dixit, “COHST and Wavelet Features Based Static ASL Numbers Recognition,” Procedia Computer Science, vol. 92, pp. 455–460, 2016.
  • K. Tripathi and N. B. G. Nandi, “Continuous Indian Sign Language Gesture Recognition and Sentence Formation,” Procedia Computer Science, vol. 54, pp. 523–531, 2015.
  • S. Rajaganapathy, B. Aravind, B. Keerthana, and M. Sivagami, “Conversation of Sign Language to Speech with Human Gestures,” Procedia Computer Science, vol. 50, pp. 10–15, 2015.
  • N. Harish and S. Poonguzhali, “Design and development of hand gesture recognition system for speech impaired people,” 2015 International Conference on Industrial Instrumentation and Control (ICIC), 2015.
  • D. Abdulla, S. Abdulla, R. Manaf, and A. H. Jarndal, “Design and implementation of a sign-to-speech/text system for deaf and dumb people,” 2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA), 2016.
  • K. Kaur and P. Kumar, “HamNoSys to SiGML Conversion System for Sign Language Automation,” Procedia Computer Science, vol. 89, pp. 794–803, 2016.
  • M. Bhuyan, C. Narra, and D. S. Chandra, “Hand gesture animation by key frame extraction,” 2011 International Conference on Image Information Processing, 2011.
  • C. Chansri and J. Srinonchat, “Hand Gesture Recognition for Thai Sign Language in Complex Background Using Fusion of Depth and Color Video,” Procedia Computer Science, vol. 86, pp. 257–260, 2016.
  • C. Amrutha, N. Davis, K. Samrutha, N. Shilpa, and J. Chunkath, “Improving Language Acquisition in Sensory Deficit Individuals with Mobile Application,” Procedia Technology, vol. 24, pp. 1068–1073, 2016.
  • P. Loke, J. Paranjpe, S. Bhabal, and K. Kanere, “Indian sign language converter system using an android app,” 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA), 2017.
  • W. Ahmed, K. Chanda, and S. Mitra, “Vision based Hand Gesture Recognition using Dynamic Time Warping for Indian Sign Language,” 2016 International Conference on Information Science (ICIS), IEEE 2016.
  • P. G. Ahire, K. B. Tilekar, T. A. Jawake, and P. B. Warale, “Two Way Communicator between Deaf and Dumb People and Normal People,” 2015 International Conference on Computing Communication Control and Automation, IEEE 2015.
  • A. A. I. Sidig, H. Luqman, and S. A. Mahmoud, “Transform-based Arabic sign language recognition,” Procedia Computer Science, vol. 117, pp. 2–9, 2017.
  • M. Alnfiai and S. Sampali, “Social and Communication Apps for the Deaf and Hearing Impaired,” 2017 International Conference on Computer and Applications (ICCA), IEEE 2017.
  • P. S. Rajam and G. Balakrishnan, “Real time Indian Sign Language Recognition System to aid deaf-dumb people,” 2011 IEEE 13th International Conference on Communication Technology, 2011.
  • W. Yang, J. Tao, and Z. Ye, “Continuous sign language recognition using level building based on fast hidden Markov model,” Pattern Recognition Letters, vol. 78, pp. 28–35, 2016.
  • P. Chavan, T. Ghorpade, and P. Padiya, “Indian sign language to forecast text using leap motion sensor and RF classifier,” 2016 Symposium on Colossal Data Analysis and Networking (CDAN), IEEE 2016.
  • N. S. Soni, M. S. Nagmode, and R. D. Komati, “Online hand gesture recognition & classification for deaf & dumb,” 2016 International Conference on Inventive Computation Technologies (ICICT), 2016.
  • S. Upendran and A. Thamizharasi, “American Sign Language interpreter system for deaf and dumb individuals,” 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), IEEE 2014.
  • S. N. Sawant and M. S. Kumbhar, “Real time Sign Language Recognition using PCA,” 2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies, IEEE 2014.
  • S. S. Shinde, R. M. Autee, and V. K. Bhosale, “Real time two way communication approach for hearing impaired and dumb person based on image processing,” 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), IEEE 2016.

Abstract Views: 412

PDF Views: 4




  • Indian Sign Language Recognition System for Deaf and Dumb Using Image Processing and Fingerspelling:A Technical Review

Abstract Views: 412  |  PDF Views: 4

Authors

Rakesh Savant
BMIIT, India
Amrutha Ajay Kunnath
Babu Madhav Institute of Information Technology, Uka Tarsadia University-Bardoli, India

Abstract


In deaf and dumb communication, they use sign language to communicate with each other. Communication is the way to convey our thoughts, message or information. Hearing and speech disabled people faces many problems when they communicate with normal people. They uses sign language person, which includes hand gesture, facial expressions, and head movement to convey their message. Using the image processing techniques, it is possible that system will be develop to help those disabled people for effective interaction with normal people. This paper compares and discusses various techniques that are used worldwide for region wise sign languages and proposed an idea that may applicable to develop a communication system for Indian Sign Language. An image processing based system can be made that will work on smartphones and will recognize sign perform by deaf-dumb and generate text or audio output for normal person and vice-versa communication.

Keywords


Sign Language, Deaf and Dumb People, Communication, Image Processing, Smartphones, Hand Gestures.

References