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Indian sign language recognition using SVM

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Abstract

Needs and new technologies always inspire people to make new ways to interact with machines. This interaction can be for a specific purpose or a framework which can be applied to many applications. Sign language recognition is a very important area where an easiness in interaction with human or machine will help a lot of people. At this time, India has 2.8M people who can’t speak or can’t hear properly. This paper targets Indian sign recognition area based on dynamic hand gesture recognition techniques in real-time scenario. The captured video was converted to HSV color space for pre-processing and then segmentation was done based on skin pixels. Also Depth information was used in parallel to get more accurate results. Hu-Moments and motion trajectory were extracted from the image frames and the classification of gestures was done by Support Vector Machine. The system was tested with webcam as well as with MS Kinect. This type of system would be helpful in teaching and communication of hearing impaired persons.

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Author information

Authors and Affiliations

  1. Machine Vision Lab CSIR-CEERI, Pilani, India

    J. L. Raheja

  2. School of Instrumentation D.A.V.V. Indore, Pilani, India

    A. Mishra

  3. Researcher, Pilani, India

    A. Chaudhary

Authors
  1. J. L. Raheja
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  2. A. Mishra
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  3. A. Chaudhary
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Corresponding author

Correspondence to J. L. Raheja.

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Jagdish Lal Raheja received his Master of Technology from Indian Institute of Technology, Kharagpur, India and Ph.D. from Technical University of Munich, Germany. Currently he is Senior Principal Scientist at Digital Systems Group, Central Electronics Engineering Research Institute (CEERI), Pilani, India. He has been a DAAD fellow and visiting scientist to many countries. He has published more than 100 papers in International Journals and peer reviewed conferences. His areas of research interest are digital image processing, embedded systems and human computer interface. He is in the editorial board of several international journals and also reviewer for many reputed conferences. He has been Principal investigator in many important real life projects.

Anand Mishra is working toward his Master of Technology in Instrumentation Engineering from School of Instrumentation, Devi Ahilya Vishwavidyalaya, Indore, INDIA. His areas of research interest are digital image processing, artificial intelligence, VLSI systems, and digital communication.

Ankit Chaudhary received his Master of Engineering in Computer Science and Engineering from Birla Institute of Technology and Science, Pilani, and Ph.D. in Computer Vision, from Central Electronics Engineering Research Institute. His areas of research interest are computer vision, digital image processing, artificial intelligence and robotics. He is member of IEEE and also serves in the editorial board at many international journals.

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Raheja, J.L., Mishra, A. & Chaudhary, A. Indian sign language recognition using SVM. Pattern Recognit. Image Anal. 26, 434–441 (2016). https://doi.org/10.1134/S1054661816020164

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  • DOI: https://doi.org/10.1134/S1054661816020164

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