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  Authors

Atharva Shinde,Anushri Shivale,Siddhesh Phapale,Assistant Prof.Renuka Kajale

  Keywords

Real-time systems, areas of interest, convolutional neural networks, and deep learning

  Abstract


People can interact and exchange ideas and emotions through communication. The social contacts of the deaf community are hindered by multiple factors. The people converse with each other using sign language. A technology can translate sign languages into a form that is comprehensible in order to communicate with ordinary people. Developing a real- time text-to-Indian Sign Language (ISL) translation system is the aim of this project. For the most part, manual labor is used. In this paper, we describe a convolutional neural network-based deep learning method for classifying signs. We initially construct a classifier model using the numerical signs and the Python-based Keras convolutional neural network implementation. In phase two, a second real-time system was used to use skin segmentation to detect the Region of Interest in the frame that displays the bounding box. To forecast the sign, the segmented region is fed into the classifier model. The accuracy rating of the system for the same subject is 99.56% in poor light and 97.26% in high light. It was observed that the classifier improved with varying image capture angles and backgrounds. The RGB camera system is the main emphasis of our strategy.

  IJCRT's Publication Details

  Unique Identification Number - IJCRTAF02064

  Paper ID - 261060

  Author type - Indian Author

  Page Number(s) - 319-323

  Pubished in - Volume 12 | Issue 5 | May 2024

  DOI (Digital Object Identifier) -   

  No Of Downloads - 29

  Author Country - India, -, -, -, -, Science and Technology

  Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Published Paper PDF : - http://www.ijcrt.org/papers/IJCRTAF02064

  Published Paper URL: : - http://ijcrt.org/viewfull.php?&p_id=IJCRTAF02064

  Published Paper PDF Downlaod: - download.php?file=IJCRTAF02064

  Cite this article

Atharva Shinde,Anushri Shivale,Siddhesh Phapale,Assistant Prof.Renuka Kajale,   "Indian Sign Language Recognition System", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 5, pp.319-323, May 2024, Available at :http://www.ijcrt.org/papers/IJCRTAF02064.pdf

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The International Journal of Creative Research Thoughts (IJCRT) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world.

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