Indian Sign Language Automated Learning using Region Bound Algorithm
Sarita D. Deshpande1, Yashwant V. Joshi2
1Sarita D. Deshpande, Department of I.T., Progressive Education Society’s Modern College of Engineering, Pune, India.
2Yashwant V. Joshi Department of E & Tc., Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded, India.
Manuscript received on 24 August 2019. | Revised Manuscript received on 09 September 2019. | Manuscript published on 30 September 2019. | PP: 3809-3815 | Volume-8 Issue-11, September 2019. | Retrieval Number: K22100981119/2019©BEIESP | DOI: 10.35940/ijitee.K2210.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents a novel technique to Indian sign language detection for automated learning to develop an interface towards elimination of communication gap between vocally disabled and common individual. In the approach of sign language detection, learning approach, decision making and processing overhead are of major concern. In this paper, a representation of sign language symbol for automated sign language detection and decision making is proposed. The proposed system is evaluated on hand based symbols of Indian sign language.
Keywords: Automated learning, Indian sign language, Region bound approach.
Scope of the Article: Natural Language Processing and Machine Translation