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Indian Sign Language Recognition Based on Gray Level Co-occurrence Matrix and 7Hu Moment

Umang Patel, Aarti G. Ambekar. Published in Information Systems.

Communications on Applied Electronics
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Umang Patel, Aarti G. Ambekar
10.5120/cae2017652649

Umang Patel and Aarti G Ambekar. Indian Sign Language Recognition Based on Gray Level Co-occurrence Matrix and 7Hu Moment. Communications on Applied Electronics 7(4):44-49, July 2017. BibTeX

@article{10.5120/cae2017652649,
	author = {Umang Patel and Aarti G. Ambekar},
	title = {Indian Sign Language Recognition Based on Gray Level Co-occurrence Matrix and 7Hu Moment},
	journal = {Communications on Applied Electronics},
	issue_date = {July 2017},
	volume = {7},
	number = {4},
	month = {Jul},
	year = {2017},
	issn = {2394-4714},
	pages = {44-49},
	numpages = {6},
	url = {http://www.caeaccess.org/archives/volume7/number4/753-2017652649},
	doi = {10.5120/cae2017652649},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Communication is an important part of our day to day life. But it is very challenging for normal people to communicate with deaf, dumb &blind people & vice versa. This is because of a deaf, dumb need sign language for communication and normal people cannot understand sign language easily. Therefore there is a demand of converting and translating sign languages. This paper removes the barrier of communication between them. In this paper, hand gestures are captured, processed and then translated into speech & text. In the proposed method, two languages for a character as well as words are chosen namely English & Hindi. Feature extraction is done using moment technique and gray level co-occurrence matrix. Two classification techniques (PNN & KNN) are used & performance parameters are compared between both classifiers.

References

  1. Cheok Ming Jin, Zaid Omar & Mohamed Hisham Jaward, ”A Mobile Application of American Sign Language Translation via Image Processing Algorithms” 2016 IEEE Region 10 Symposium (TENSYMP), Bali, Indonesia
  2. Rohit Rastogi ,Shashank Mittal & Sajan Agarwal “ Novel Approach for Communication among Blind, Deaf and Dumb People” 2015 2nd International Conference on Computing for Sustainable Global Development
  3. Suganya R & Dr. T.Meeradevi “Design Of a Communication aid for physically challenged” Ieee Sponsored 2nd International Conference On Electronics And Communication System (ICECS 2015)
  4. Kusurnika Krori Dutta, Satheesh Kumar Raju, Anil Kumar G, Sunny Arokia Swarny “Double Handed Indian Sign Language to Speech and Text” 2015 Third International Conference on Image Information Processing
  5. Piotr Muzyka, Marek Frydrysick & Elzbieta Roszkowska “Real-Time Detection of Hand Gestures”.
  6. Priyanka C Pankajakshan & Thilagavathi B ”Sign Language Recognition system” IEEE Sponsored 2nd International conference ICIIECS’15
  7. Prof. Prashant G. Ahire, Kshitija B. Tilekar, Tejaswini A. Jawake, Pramod B. Warale “Two Way Communicator Between Deaf and Dumb People And Normal People”. 2015 International Conference on Computing Communication Control and Automation
  8. Ashish s. Nikam & Aarti G. Ambekar “Bilingual Sign Recognition Using Image Based Hand Gesture Technique for Hearing and Speech Impaired People” IEEE 2nd International conference on Computing, Communication, Control & Automation. Aug 2016.
  9. Ashish s. Nikam & Aarti G. Ambekar “Sign language recongization using image based hand gesture recongnition techniques” IEEE 3rd International conference on Innovation in Information, Embedded & Communication system (ICIIECS’16).
  10. P. Suresh, N. Vasudevan, and N. Ananthanarayanan, "Computer-aided interpreter for hearing and speech impaired," Proc. IEEE 4th Int. Con! Comput. IntelI. Commun. Syst. Networks ,CICSyN2012, pp. 248-253.
  11. A. S. Ghotkar, R. Khatal, S. Khupase, S. Asati, and M. Hadap, "Hand gesture recognition for Indian Sign Language," IEEE Int. Conf Comput. Commun. Informatics 2012, pp. 1-4.
  12. A. Thorat, V. Satpute, A. Nehe, T.Atre Y.Ngargoje , "Indian Sign Language Recognition System for Deaf People " Int. J.Adv. compt.comm. engg.IJARCCE,pp.5319-5321 ,2014
  13. Yang quan, Peng jinye, Li yulong“Chinese Sign Language Recognition Based on Gray-Level Co-Occurrence Matrix and Other Multi-features Fusion”ICIEA 2009, pp 1569-1572.
  14. MATLAB/help

Keywords

Hand Gesture, Sign Recognition, Image Processing, Indian Sign Language (ISL), 7Hu Moments, KNN Classifier, PNN Classifier, GLCM.