Statistics

    Map

Twitter

Support Vector Machine based Image Classification for Deaf and Mute People
( Vol-5,Issue-4,April 2018 )
Author(s):

Mr. J. Jijin Godwin, Pavithra S, Nandini S, Shree Shankari R

Keywords:

Sign language, SVM (support vector machine), gesture recognition, feature extraction, gray illumination algorithm.

Abstract:

A hand gesture recognition system provides a natural, innovative and modern way of nonverbal communication. It has a wide area of application in human computer interaction and sign language. The whole system consists of three components: hand detection, gesture recognition and human-computer interaction (HCI) based on recognition; in the existing technique, ANFIS(adaptive neuro-fuzzy interface system) to recognize gestures and makes it attainable to identify relatively complex gestures were used. But the complexity is high and performance is low. To achieve high accuracy and high performance with less complexity, a gray illumination technique is introduced in the proposed Hand gesture recognition. Here, live video is converted into frames and resize the frame, then apply gray illumination algorithm for color balancing in order to separate the skin separately. Then morphological feature extraction operation is carried out. After that support vector machine (SVM) train and testing process are carried out for gesture recognition. Finally, the character sound is played as audio output.

ijaers doi crossref DOI:

10.22161/ijaers.5.4.7

Paper Statistics:
  • Total View : 146
  • Downloads : 23
  • Page No: 046-052
Cite this Article:
MLA
Mr. J. Jijin Godwin et al ."Support Vector Machine based Image Classification for Deaf and Mute People". International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),vol 5, no. 4, 2018, pp.046-052 AI Publications, doi:10.22161/ijaers.5.4.7
APA
Mr. J. Jijin Godwin, Pavithra S, Nandini S, Shree Shankari R(2018).Support Vector Machine based Image Classification for Deaf and Mute People. International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),5(4), 046-052. http://dx.doi.org/10.22161/ijaers.5.4.7
Chicago
Mr. J. Jijin Godwin, Pavithra S, Nandini S, Shree Shankari R. 2018,"Support Vector Machine based Image Classification for Deaf and Mute People". International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)).5(4):046-052. Doi: 10.22161/ijaers.5.4.7
Harvard
Mr. J. Jijin Godwin, Pavithra S, Nandini S, Shree Shankari R. 2018,Support Vector Machine based Image Classification for Deaf and Mute People, International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)).5(4), pp:046-052
IEEE
Mr. J. Jijin Godwin, Pavithra S, Nandini S, Shree Shankari R."Support Vector Machine based Image Classification for Deaf and Mute People", International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),vol.5,no. 4, pp.046-052,2018.
Bibtex
@article {mr.j.jijingodwin2018support,
title={Support Vector Machine based Image Classification for Deaf and Mute People},
author={Mr. J. Jijin Godwin, Pavithra S, Nandini S, Shree Shankari R},
journal={International Journal of Advanced Engineering Research and Science},
volume={5},
year= {2018},
}
Share:
References:

[1] Aditi Kalsh, N.S. Garewal,” Sign Language Recognition System for Deaf and Dumb”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, Issue. 9, pp. 103-106.
[2] Shreyashi Narayan Sawant(May 2014), “Sign language recognition system to aid deaf-dumb people using PCA.”, International Journal of Computer Science & Engineering Technology, vol. 5, No. 5, pp. 570-574
[3] Jyoeta Singha and Karen Das May 2013. “Recognition of Indian sign Language in live video. ”, International Journal of Computer Applications, vol 70, No. 19, pp.17-22.
[4] P. V .V. Kishore and P. Rajesh Kumar (Oct 2012), “A video based Indian sign language recognition system (INSLR) using wavelet transform and fuzzy logic.” International Journal of Engineering and Technology, vol.4, no. 5, , pp.537-542.
[5] Anup Nandy, Jay Shankar Prasad, Soumik Mondal, Pavan Chakraborty and G.C. Nandi (2010). “Recognition of isolated Indian sign language gesture in real time” Information Processing and Management. Springer Berlin Heidelberg. pp. 102-107.
[6] Kunal Wankhade , Prof. Gauri Zade.( May 2014), “Sign Language Recognition for Deaf And Dumb People Using ANFIS”, International Journal of Science , Engineering and Technology Research, Vol. 3, Issue.5, pp.1206-1210.
[7] Ashish Sethi ,Hemanth S, Kuldeep Kumar, Bhaskara Rao N, Krishnan R (May 2012), “ Sign Pro-An Application Suite for Deaf and Dumb ”, IJCSET, vol. 12, No. 5, pp. 1203-1206.
[8] Kumud Tripathi, and Neha Baranwal, G.C Nandi(2015). “Continuous Indian Sign Language Gesture Recognition and Sentence Formation.” Procedia Computer Science 54: 523-531.
[9] Chandandeep Kaur, Nivit Gill(May 2015). “An Automated System for Indian Sign Language Recognition.” International Journal Of Advanced Research in Computer Science and Software Engineering, Vol. 5, Issue.5, pp. 1037-1042.
[10] Sangeetha, K. and Barathi Krishna, L (March, 2014), “Gesture detection for deaf and dumb people”, International Journal of Development Research, Vol. 4, Issue 3, pp. 749-752.
[11] [13] Ahire, Prashant G.(2015) “ Two Way Communicator between Deaf and Dumb People and Normal People" ,Computing Communication Control and Automation (ICCUBEA), 2015, International Conference on. IEEE.
[14] M. Sushmita, A. Tinku (May 2007), “Gesture Recognition: A Survey”, IEEE transactions on systems, man, and cybernetics—part c: applications and reviews, vol. 37, issue 3, pp. 311-324.
[15] Suganya, R. and Meeradevi, T., 2015, February. “Design of a Communication aid for physically challenged”, In Electronics and Communication Systems (ICECS), International Conference on pp.818-822, IEEE.
[16] WEBSITE: HTTP://WWW.PRI.ORG/STORIES/2017-01-04/DEAF Community-millions-hearing-India only just beginning-sign.
[17] Website: http://wfdeaf.org/human-rights/crpd/sign-language/#