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Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 1, Pages 96-115, DOI: https://doi.org/10.21307/ijssis-2017-647
License : (CC BY-NC-ND 4.0)
Received Date : 03-January-2014 / Accepted: 14-February-2014 / Published Online: 27-December-2017
Human Computer Interaction moves forward in the field of sign language interpretation.Indian Sign Language (ISL) Interpretation system is a good way to help the Indian hearing impaired people to interact with normal people with the help of computer. As compared to other sign languages, ISL interpretation has got less attention by the researcher. In this paper, some historical background, need, scope and concern of ISL are given. Vision based hand gesture recognition system have been discussed as hand plays vital communication mode. Considering earlier reported work, various techniques available for hand tracking, segmentation, feature extraction and classification are listed. Vision based system have challenges over traditional hardware based approach; by efficient use of computer vision and pattern recognition, it is possible to work on such system which will be natural and accepted, in general.
 U. Zeshan, “ ‘A’ level Introductory course in INDIAN SIGN LANGUAGE”, Ali Yavar Jung National Institute for Hearing Handicapped, Mumbai, 2001, pp. 1-38.
 P. Garg, N. Agrawal, S. Sofat, “Vision based Hand Gesture Recognition”, Proceedings of world Academy of Science, Engineering and Technology, Vol.37, 2009, pp. 1024-1029.
 U. Zeshan, M. Vasishta, M. Sethna, “Implementation of Indian Sign Language in Educational Setting”, Asia pacific Disability Rehabilitation Journal,Vo.16, No.1, 2005, pp. 16-39.
 Dasgupta, Shulka, S. Kumar, D. Basu, “A Multilingual Multimedia Indian Sign Language Dictionary Tool”, The 6th Workshop on Asian Language Resources, 2008, pp. 57-64.
 M. K. Bhuyan, D. Ghoah, P. Bora, “A Framework for Hand Gesture Recognition with Application to sign language”, India Conference, IEEE, Sept. 2006, pp. 1-6.
 P. Subha Rajan, G. Balakrihnan, “Recognition of Tamil Sign Language Alphabet using Image Processing to aid Deaf-Dumb People”, International Conference on Communication Technology and System Design, 2011, pp. 861-868.
 S. Begum, Md. Hasanuzzaman, “Computer Vision-based Bangladeshi Sign Language Recognition System”, IEEE, International conference on Computer and Information Technology,2009, pp. 414-419.
 T. Swee, Selleh, Ariff, Ting, Seng, “Malay sign Language Gesture Recognition System”,International Conference on Intelligent and Advanced System, IEEE, 2007, pp. 982-985.
 T. Shanableh, K. Assaleh, “Arabic sign language recognition in user independent mode”,International conference on Intelligent and Advanced Systems, 2007, pp. 597-600.
 Maryam,Mansour,Majid, “Sign Language Recognition”, Signal Processing and It’s Applications, IEEE, ISSPA, 2007, pp. 1-4.
 Satjakarn, V. Jailongrak, S. Thiemjarus, “An Assistive Body Sensor Network Glove for Speech and Hearing–Impaired Disabilities”, International Conference on Body Sensor Networks,IEEE Computer Society, 2011, pp. 7-12.
 M. M. Zaki, S. Shaheen, “Sign language recognition using a combination of new vision based features”, Pattern Recognition Letters, Elsevier, 2011, pp. 572-577.
 H. Pistori, J. Neto, “An Experiment on Hand shape Sign Recognition Using Adaptive Technology: Preliminary Results”, SBIA, LNAI 3171, 2004, pp. 464-473.
 W. Gao, Fang, Zhao, Chen, “A Chinese sign language recognition system based on SOFM/SRN/HMM”, The Journal of the Pattern Recognition Society, 2004, pp. 2389-2402.
 C. Vogler, D. Metaxas, “A Framework for Recognizing the Simultaneous Aspects of American Sign Language”, Computer Vision and Image Understanding, 2001, pp. 358-384.
 Q. Munib, Moussa, Bayan, Hiba, “American Sign Language(ASL) recognition based on Hough transform and neural network”, Expert Systems with Applications, Elsevier, 2007, pp. 24-37.
 D. Tewari, S. Kumar, “A Visual Recognition of Static Hand Gesture in Indian Sign Language based on Kohonen Self organizing Map Algorithm”, International Journal of Engineering and Advanced Technology, ISSN: 2249-8958, Vol-2, Issue-2, , 2012, pp. 165-170.
 J. Napier, Hands. New York: Pantheon Books, 1980
 L. Howe, F. Wong, A. Chekima, “Comparison of Hand Segmentation Methodologies for Hand Gesture Recognition”, Information Technology, ITSIM, IEEE-978-4244-2328-6, 2008, pp.1-7.
 V. Vezhnevets, V. Sazonov.and A. Andreeva, “ A Survey on Pixel-Based Skin color Detection Techniques”, In Proceedings of Graphicon, 2003, pp. 85-92.
 S. Phung, A. Bouzerdoum and D. Chai, “Skin Segmentation Using Color Pixel Classification: Analysis and Comparison”, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol.27, No. 1, 2005, pp. 148-154.
 G. Yang, H. Li, L. Zhang and Y. Cao, “Research on a Skin Color Detection Algorithm Based on Self-adaptive Skin Color Model”, IEEE , International Conference on Communications and Intelligence Information, Oct. 2010, pp. 266 – 270.
 S. Tsagaris, S. Manitsari, “Color Spaces Comparisons for Skin Detection in Finger Gesture Recognition”, International Journal of Advances in Engineering & Technology, 2013, pp. 1431-1441.
 A. Elgammal, C. Muang and D. Hu, “Skin Detection – a Short Tutorial”, Encyclopedia of Biometrics, Springer-Verlag Berlin Heidelberg, 2009, pp. 1-10.
 C. Jung, C. Kim, S. Chae, and S. Oh, “Unsupervised Segmentation of Overlapped Nuclei Using Bayesian Classification”, IEEE Transaction on Biomedical Engineering, Vol. 57, No.12,Dec-2010, pp. 2825-2832.
 H. Rahimizadeh, M. Marhaban, R. Kamil, and N. Ismail, “Color Image Segmentation Based on Bayesian Theorem and Kernel Density Estimation”, European Journal of Scientific Research,ISSN 1450-216, vol.26, No.3, 2009, pp. 430-436.
 A. Chitade, S. Katiyar, “Color Based Image Segmentation Using K-means Clustering”,International Journal of Engineering Science and Technology, Vol.2, No.10, 2010, pp. 5319-5325.
 A. Yilmaz, O. Javed, M. Shah, “Object Tracking: A Survey”, ACM Computing Surveys,Vol. 38, No. 4, Article 13, December 2006, pp. 1-45.
 D. Comaniciu, V. Ramesh, and P. Meer, “Real-time tracking of non-rigid objects using mean shift”, Computer Vision and Pattern Recognition Proceedings, Volume 2, 2000, pp. 142-149.
 A. S. Ghotkar , G. K. Kharate, “Hand Segmentation Techniques to Hand Gesture Recognition for Natural Human Computer Interaction”, International Journal of Human Computer Interaction(IJHCI), Computer Science Journal, Malaysia, Volume 3, no. 1, ISSN 2180-1347, April 2012, pp. 15-25.
 L. Yun, Z. Peng, “An Automatic Hand Gesture Recognition System based on viola-Jones Method and SVMS”, International workshop on Computer Science and Engineering, IEEE Computer Society, 2009, pp. 72-76.
 Ayan, Pragya, Rohot, “Information Measure Ratio Based Real Time Approach for Hand Region Segmentation with a Focus on Gesture Recognition”, Second International Conference on Intelligent System, Modeling and Simulation, IEEE computer Society, 2011, pp. 172-176.
 Surachai, Stewart, Ahmet, “Two Hand Tracking using Color Statistical Model with the Kmeans Embedded Particle Filter for Hand Gesture Recognition”, 7th Computer Information Systems and Industrial Management Applications, 2008, pp. 201-205.
 Pham, Nguyen, TuKhoa, “A New Approach to Hand Tracking and Gesture Recognition by a New Feature Type and HMM”, Sixth International Conference on Fuzzy Systems and Knowledge Discovery, IEEE Computer Society, 2009, pp. 3-6.
 Chueh-Wei, Chun-Hao, “A Two-Hand Multi-Point Gesture Recognition System Based on Adaptive Skin Color Model”, IEEE, 2011, pp. 2901-2904.
 M. Ho, Yoshinori, Nobutaka, “Two-Hand Gesture Recognition using Coupled Switching Linear model”, IEEE, 2002, pp. 529-532.
 D. Zhang, C. Lu, “Review of shape representation and description techniques”, The Journal of the Pattern Recognition Society, Elsevier, 2004, pp. 1-19.
 U. Rokade, D. Doye, M. Kokare, “Hand Gesture Recognition Using Object Based Key Frame Selection”, International Conference on digital Image Processing, IEEE Computer Society, 2009, pp. 228-291.
 W. Chung, X. Wu, Y. Xu. , “A Real time Hand Gesture Recognition based on Haar wavelet Representation”, Proceedings of the IEEE-International Conference on Robotics and Biometrics,Bangkok, Thailand, 2008, pp. 336-341.
 N. D. Binh, E. Shuichi, T. Ejima, “Real time Hand Tracking and Gesture Recognition System”, ICGST International Conference on Graphics, Vision and Image Processing, GVIP 05 Conference, Egypt, Dec-2005, pp. 362-368.
 T. Maung, “Real-Time Hand Tracking and Gesture Recognition System Using Neural Networks”, PWASET, Volume 38, 2009, pp. 470-474.
 Y. Quan, P. Jinye, L.Yulong, “Chinese Sign Language Recognition Based on Gray Level Co-Occurrence Matrix and Other Multifeatures Fusion”, IEEE-ICIEA, 2009, pp.1569-1572.
 U. Rokade, D. Doye, M. Kokare, “Hand Gesture Recognition by thinning method”International Conference on digital Image Processing, IEEE Computer Society, 2009. pp. 284-287.
 A. K. Jain, R. Duin, Mao, “Statistical Pattern Recognition: A Review”, IEEE Transactions On Pattern Analysis And Machine Intelligence, Volume 22, No. 1, January 2000. pp. 4-37.
 J. Li, B. Lu, “An adaptive image Euclidean distance”, Pattern Recognition Journal, Elsevier, Volume 42, 2009, pp. 349 -357.
 Guo-Dong, A. K. Jain, W. Ma, H. Zhang, “Learning similarity Measure for Natural Image Retrieval with Relevance Feedback”, IEEE Transactions on Neural Networks, Vol.13, No. 4, July 2002, pp. 811-820.
 K. K. Wong, R. Cipolla, “Continuous gesture recognition using a sparse Bayesian classifier”, International conference on pattern recognition, 2006, pp. 1084-1087.
 T. Maung, “Real-Time Hand Tracking and Gesture Recognition System Using Neural Networks”, PWASET, Vol.38, 2009, pp. 470-474.
A. Corradini, “Real-Time Gesture Recognition by means of Hybrid Recognizers”, GW 2001, LNAI 2298, Springer-Verlag Berlin Heidelberg 2002, pp. 34-47.
P. Bao, N. Binh, T. Khoa, “A new Approach To Hand Tracking and Gesture Recognition By A New Feature Type And HMM”, International Conference on Fuzzy Systems and Knowledge Discovery, IEEE Computer Society, 2009, pp. 3-6.
 N. Saliza, J. Jais,, L. Mazalan, R. Ismail, S. Yussof, A. Ahmad, A. Anuar, D. Mohamad,“Hand Gesture Recognition using Hidden Markov Models: A Review on Techniques and Approaches” , The Second Malaysian Software Engineering Conference, Dec. 2006, pp.1-6.
 A. Braffort, “Research on Computer Science and Sign Language; Ethical Aspect” LNAI 2298, Springer, LANI-2298, GW-2001, pp. 1-8.
 B. Bauer , Karl-Friedrich, “Towards an Automatic Sign Language Recognition System Using Subunits”, LNAI 2298, GW-2001, Springer, pp. 34-47.
 F. Karray, M. Alemzadeh, J. A. Saleh and M. Nours, “Human-Computer Interaction:Overview on State of the Art”, International Journal on Smart Sensing and Intelligent System,Vol.1, No.1, March 2008, pp. 137-159.
 A. S. Ghotkar and G. K. kharate, “Vision based Hand Gesture Recognition Techniques for Human Computer Interaction.”, International Journal of Computer Application, Computer Science Foundation, New York, USA, Volume: 70, No. 6, ISSN:0975 -8887, May-2013, pp. 1-6.
 T. Ikai1, M. Ohka1, S. Kamiya1, H. Yussof and S. C. Abdullah, “Evaluation of Finger Direction Recognition Method for Behavior Control of Robot”, International Journal on Smart Sensing and Intelligent System, Volume. 6, No. 5, December 2013, pp. 2308-2333.
 L. Silvia, “Audiovisual Sensing of Human Movements for Home-Care And Security in a Smart Environment”, International Journal on Smart Sensing and Intelligent System, Volume 1,No. 1, March 2008, pp. 220-245.