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Distinctive Feature Extraction for Indian Sign Language (ISL) Gesture using Scale Invariant Feature Transform (SIFT)

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Abstract

India, having less awareness towards the deaf and dumb peoples leads to increase the communication gap between deaf and hard hearing community. Sign language is commonly developed for deaf and hard hearing peoples to convey their message by generating the different sign pattern. The scale invariant feature transform was introduced by David Lowe to perform reliable matching between different images of the same object. This paper implements the various phases of scale invariant feature transform to extract the distinctive features from Indian sign language gestures. The experimental result shows the time constraint for each phase and the number of features extracted for 26 ISL gestures.

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References

  1. G.R. Sinha, S. B. Patil, Biometrics: Concept and Application, Wiley India Pvt. Ltd (2013)

  2. V.J. Arulkarthick, D. Sangeetha, S. Umamaheswari, Sign language recognition using K-means clustered Haar-like features and a stochastic context free grammar. Eur. J. Sci. Res. 78(1), 74–84 (2012)

    Google Scholar 

  3. J. Alon, V. Athitsos, A unified framework for gesture recognition and spatiotemporal gesture segmentation. IEEE Trans. Pattern Anal. Med. Intell. 31(9), 1685–1699 (2009)

    Article  Google Scholar 

  4. M.K. Bhuyan, M.K. Kar, R.N. Debanga, Hand pose identification from monocular image for sign language recognition, IEEE international conference on signal and image processing applications (ICSIPA2011), 3(12), 378–383 (2011)

  5. G. Balakrishnan, P.S. Rajam, Real time Indian sign language recognition system to aid deaf-dumb people, IEEE international conference on computing communication and networking technologies (ICCCNT), 737–742 (2011)

  6. P. Chakraborty, S. Mondal, A. Nandy, J.S. Prasad, Recognizing and interpreting Indian sign language gesture for human robot interaction, Int’l conference on computer and communication technology |ICCCT’10|, 712–717 (2010)

  7. S. Jothilakshmi, S. Palanivel, V. Ramalingam, A hierarchical language identification system for Indian languages. Digit. Signal Proc. 2(2), 544–553 (2012)

    Article  MathSciNet  Google Scholar 

  8. P.V.V. Kishore, P.R. Kumar, A video based Indian sign language recognition system (INSLR) using wavelet transform and fuzzy logic. Int. J. Eng. Technol. 4(5), 537–542 (2012)

    Article  Google Scholar 

  9. P.V.V. Kishore, P.R. Kumar, Segment, track, extract, recognize and convert sign language videos to voice/text. Int. J. Adv. Comput. Sci. Appl. 3(6), 35–47 (2012)

    MathSciNet  Google Scholar 

  10. M. Krishnaveni, V. Radha, Classifier fusion based on Bayes aggregation method for Indian sign language datasets. Proc. Eng. 30, 1110–1118 (2012)

    Article  Google Scholar 

  11. A. Magdy, A. Samir, Error detection and correction approach for Arabic sign language recognition, ISSN 978-1-4673-2961, 3(12), 117–123 (2012)

  12. U. Zeshan, M.M. Vasishta, M. Sethna, Implementation of Indian sign language in educational settings. Asia Pac. Disabil. Rehabil. J. 16(1), 16–40 (2005)

    Google Scholar 

  13. S. Majumder, J. Rekha, Indian sign language recognition with global-local hand configuration, IEEE 13th international conference on communication technology (ICCT), 27–33 (2011)

  14. T.D. Nguyen, S. Ranganath, Facial expressions in American sign language: tracking and recognition. Pattern Recognit. 45(5), 1877–1891 (2012)

    Article  MATH  Google Scholar 

  15. M.P. Paulraj, R. Palaniappan, S. Yaacob, A. Zanar, A phoneme based sign language recognition system using 2D moment invariant interleaving feature and neural network. IEEE Stud. Conf. Res. Dev. 2(11), 111–116 (2011)

    Google Scholar 

  16. A.S. Ghotkar, M. Hadap, R. Khatal, S. Khupase, Hand gesture recognition for Indian sign language, International conference on computer communication and informatics (ICCCI -2012), Coimbatore, India, 2(4), 9–12 (2012)

  17. Y. Quan, Chinese sign language recognition based on video sequence appearance modeling, Fifth IEEE conference on industrial electronics and applications, ISSN 978-1-4244-5046-6/10:1537–1542 (2010)

  18. A. Bhosekar, K. Kadam, R. Ganu, S.D. Joshi, American sign language interpreter. IEEE Fourth Int. Conf. Technol. Educ. 6(12), 157–159 (2012)

    Google Scholar 

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Authors and Affiliations

  1. Shri Shankaracharya Technical Campus, Shri Shankaracharya Group of Institutions, Bhilai, India

    Sandeep Baburao Patil & G. R. Sinha

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  1. Sandeep Baburao Patil
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  2. G. R. Sinha
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Correspondence to Sandeep Baburao Patil.

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Patil, S.B., Sinha, G.R. Distinctive Feature Extraction for Indian Sign Language (ISL) Gesture using Scale Invariant Feature Transform (SIFT). J. Inst. Eng. India Ser. B 98, 19–26 (2017). https://doi.org/10.1007/s40031-016-0250-8

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  • DOI: https://doi.org/10.1007/s40031-016-0250-8

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