ML based sign language recognition system

Title

ML based sign language recognition system

Creator

Amrutha K.; Prabu P.

Description

This paper reviews different steps in an automated sign language recognition (SLR) system. Developing a system that can read and interpret a sign must be trained using a large dataset and the best algorithm. As a basic SLR system, an isolated recognition model is developed. The model is based on vision-based isolated hand gesture detection and recognition. Assessment of ML-based SLR model was conducted with the help of 4 candidates under a controlled environment. The model made use of a convex hull for feature extraction and KNN for classification. The model yielded 65% accuracy. 2021 IEEE.

Source

2021 International Conference on Innovative Trends in Information Technology, ICITIIT 2021

Date

2021-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Automated SLR; Classification models; Feature extraction; Preprocessing; Segmentation

Coverage

Amrutha K., CHRIST(Deemed to Be University), Dept. of Computer Science, Bangalore, India; Prabu P., CHRIST(Deemed to Be University), Dept. of Computer Science, Bangalore, India

Rights

Restricted Access

Relation

ISBN: 978-166540467-9

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICITIIT51526.2021.9399594

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