Human hands are delicate instruments. Hand gestures and finger gestures are excellent ways of emphasizing what we say, but on the other hand they can also reveal our true intentions. In this paper introduced a continuous Indian sign language recognition system, wherever each the hands are used for playacting any gesture. Recognizing a sign language gestures from continuous gestures could be a terribly difficult analysis issue. This paper solve the problem using gradient based key frame extraction technique. These key frames are useful for splitting continuous language gestures into sequence of signs further as for removing uninformative frames. After splitting of gestures every sign has been treated as associate degree isolated gesture. Then features of pre-processed gestures are extracted using orientation histogram (OH) with principal component analysis (PCA) is applied for reducing dimension of features obtained after OH. Experiments are performed on our own continuous ISL dataset which is created using EOS camera in PG Research Laboratory (SPPU, Pune). Probes are tested exploitation varied forms of classifiers like, Manhattan distance, Correlation, Manhattan distance, City block distance, Euclidian distance etc. Comparative analysis of our projected theme is performed with varied forms of distance classifiers. From this analysis we tend to found that the results obtained from Correlation and Euclidian distance offers higher accuracy then alternative classifiers.

Gesture Recognition, Orientation histogram (OH); Correlation; Indian sign language (ISL); Principal component analysis (PCA);

[1] M. Mohandes, M. Deriche, and J. Liu, �Image-Based and Sensor-Based Approaches to Arabic Sign Language Recognition�, In Proc. IEEE Transaction on Human Machine System, ,pp.2168-2291, 2014.
[2] P. Nanivadekar and V. Kulkarni, �Indian Sign Language Recognition: Database creation, Hand Tracking and Segmentation � , in IEEE Conference On Circuit System, Communication And Information Technology Applications, 2014,
[3] K.Modi and A More, �Translation of Sign Language Finger-Spelling to Text using Image Processing�, In conference (IJCA), Volume 77, No.11, September, 2013.
[4] S .N . Omkar and M. Monisha,� Sign Language Recognition Using Thinning Algorithm�, ICTACT Journal On Image And Video Processing, Volume 02, Issue: 01� August 2011.
[5] S. Nagarajan and T. S. Subashini, �Static Hand Gesture Recognition for Sign Language Alphabets using Edge Oriented Histogram and Multi Class SVM�, International Journal of Computer Applications (0975 �8887),Volume 82, No4, November 2013.
[6] G. R. S. Murthy and R. S. Jadon , �Hand gesture recognition using neural networks�, Advance Computing Conference (IACC), IEEE 2nd International Conference, Patiala, pp 134 � 138, Feb2010.
[7] Nashwa El-Bendary , Hossam M. Zawbaa , Mahmoud S. Daoud and Aboul Ella Hassanien, �ArSLAT: Arabic Sign Language Alphabets Translator�, Computer Information Systems and Industrial Management Applications (CISIM), 2010 International Conference on Date of Conference:8-10 Oct. 2010 Page(s):590-595 Conference Location:Krackow Publisher:IEEE.
[8] Haitham Hasan and S. Abdul-Kareem, �Static hand gesture recognition using neural networks�, Spinger link: Artificial Intelligence Review February 2014, Volume 41, Issue 2, pp 147�181.
[9] Ramesh Kagalkar and Dr. Nagaraja H.N, �New Methodology for Translation of Static Sign Symbol to Words in Kannada Language�,� International Journal of Computer Applications(IJCA), Volume 121, No.20,PageNo. 25-30, July-2015.
[10] Ramesh M. Kagalkar, Dr. Nagaraja H.N and Dr. S.V Gumaste�,A Novel Technical Approach for Implementing Static Hand Gesture Recognition�, International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), Volume 4, Issue 7, July 2015.
[11] Ramesh M. Kagalkar and Dr. S.V Gumaste, �Automatic Graph Based Clustering for Image Searching and Retrieval from Database�, CiiT International Journal of Software Engineering and Technology, Volume 8, No 2, 2016.
[12] Ramesh M. Kagalkar and Dr. S.V Gumaste, �Review Paper: Detail Study for Sign Language Recognition Techniques�, CiiT International Journal of Digital Image Processing, Volume 8, No 3, 2016.
[13] Rashmi B. Hiremath and Ramesh Kagalkar, �A Methodology for Sign Language Video Analysis and Translation into Text in Hindi Language�,CiiT International Journal of Fuzzy System, Volume 8, No 5, 2016.
[14] Rashmi B. Hiremath and Ramesh Kagalkar, �Methodology for Sign Language Video Interpretation in Hindi Text Language�, International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE), Volume. 4, Issue 5, May 2016.
[15] Amitkumar and Ramesh Kagalkar, �Sign Language Recognition for Deaf User�, Internal Journal for Research in Applied Science and Engineering Technology (IJRASET), Volume 2, Issue 12, December 2014.
[16] Amit kumar and Ramesh Kagalkar, �Advanced Marathi Sign Language Recognition using Computer Vision�, International Journal of Computer Applications (IJCA), Volume 118, No. 13, May 2015.
[17] Amit kumar and Ramesh Kagalkar, �Methodology for Translation of Sign Language into Textual Version in Marathi�, CiiT, International Journal of Digital Image Processing, Volume 07, No.08, Aug 2015.
[18] Mrunmayee and Ramesh Kagalkar, �A Review On Conversion of Image To Text as Well as Speech using Edge Detection and Image Segmentation�, International Journal of Science and Research (IJSR), Volume 3, Issue 11, November 2014.
[19] Mrunmayee Patil and Ramesh Kagalkar, �An Automatic Approach for Translating Simple Images into Text Descriptions and Speech for Visually Impaired People�, International Journal of Computer Applications (IJCA), Volume 118, No. 3, May 2015.
[20] Kaveri Kamble and Ramesh Kagalkar, �A Review: Translation of Text to Speech Conversion for Hindi Language�, International Journal of Science and Research (IJSR), Volume 3, Issue 11, November 2014.
[21] Kaveri Kamble and Ramesh Kagalkar, �Audio Visual Speech Synthesis and Speech Recognition for Hindi Language� ,International Journal of Computer Science and Information Technologies (IJCSIT), CiiT International Journal of Data Mining Knowledge Engineering, Volume 6, Issue 2, April 2015.
[22] Kaveri Kamble and Ramesh Kagalkar � A Novel Approach for Hindi Text Description to Speech and Expressive Speech Synthesis� International Journal of Applied Information Systems (IJAIS), Volume 8, No.7, May 2015.
[23] Shivaji Chaudhari and Ramesh Kagalkar �A Review of Automatic Speaker Recognition and Identifying Speaker Emotion Using Voice Signal�, International Journal of Science and Research (IJSR), Volume 3, Issue 11, November 2014.
[24] Shivaji Chaudhari and Ramesh Kagalkar, �Automatic Speaker Age Estimation and Gender Dependent Emotion Recognition�, International Journal of Computer Applications (IJCA), Volume 117, No. 17, May 2015.
[25] Shivaji J. Chaudhari and Ramesh M Kagalkar, �A Methodology for Efficient Gender Dependent Speaker Age and Emotion Identification System�, International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), Volume 4, Issue 7, July 2015.
[26] Ajay R. Kadam and Ramesh Kagalkar, �Audio Scenarios Detection Technique�, International Journal of Computer Applications (IJCA), Volume 120, No. 16, June 2015.
[27] Ajay R. Kadam and Ramesh Kagalkar, �Predictive Sound Recognition System�, International Journal of Advance Research in Computer Science and Management Studies (IJARCSMS), Volume 2, Issue 11.
[28] Swati Sargule and Ramesh M Kagalkar, �Hindi Language Document Summarization using Context Based Indexing Model�, CiiT International Journal of Data Mining Knowledge Engineering, Volume 08, No. 01, Jan 2016.
[29] Swati Sargule and Ramesh M Kagalkar, �Methodology of Context Centered Term Indexing Style Intended For Hindi Language Document Summarization�, CiiT International Journal of Software Engineering, Volume 8, No 5, 2016.
[30] Vandana D. Edke and Ramesh M. Kagalkar, �Video Object Description of Short Videos in Hindi Text Language�, International Journal of Computational Intelligence Research, Volume 12, Number 2 (2016), pp. 103-116 � Research India Publications.