Title: Curvilinear tracing approach for recognition of Kannada sign language

Authors: Ramesh M. Kagalkar; Shyamrao V. Gumaste

Addresses: VTU-RRC, Visvesvaraya Technological University (VTU), Belgaum, Karnataka, India ' VTU-RRC, Visvesvaraya Technological University (VTU), Belgaum, Karnataka, India

Abstract: Sign languages are used as the main mode of communication for vocally disabled people; however, the diversity in sign symbol representation limits its usage to a particular region. There is a huge diversity in sign symbol representation from one country to another, one state to another. In India there are different sign languages observed for each state region. It is hence very difficult for one region individual to communicate to another using a significant symbol. This paper proposes a curvilinear tracing approach for shape representation and recognition of Kannada sign language to generate corresponding characters in Kannada language. To develop this approach, a dataset is created with all Swaragalu, Vyanjanagalu, and numbers in Kannada language. The dataset is formed by defining a vocabulary for different sign symbols used in common interfacing. In the representation of sign language for recognition, edge features of hand regions are considered to be an optimal feature representation of sign language.

Keywords: curvilinear feature; leap forward tracing; SVM; support vector machine.

DOI: 10.1504/IJCAT.2019.097119

International Journal of Computer Applications in Technology, 2019 Vol.59 No.1, pp.21 - 30

Received: 20 Jan 2017
Accepted: 03 Jan 2018
Published online: 21 Dec 2018 *

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