Abstract

In this paper, we present an finger point based signed language symbol to text identification and classification algorithm that is based upon RGB image datasets. The palm sized images based upon different sizes, backgrounds, orientation are captured to be preprocessed as per the requirements of developing a convolution neural network based algorithm. This algorithm utilizes Alexnet for the preprocessing requisites where in 47 symbols of Devanagari script are augmented based on the reference rulebook created for our requirements as highlighted in the paper. At the primary level this algorithm provides an excellent classification rate which promises upliftment for our research in the upcoming future. We have provided detailed steps and discussion on the classification parameters considered for our algorithm which is implemented on MATLAB platform with the help of machine learning solution libraries.

Details

Title
An Approach to Pattern Recognition for Identification of Devnagari Script Based on Fingertips and Palm
Author
Tantarpale, Sharvari 1 ; Deshmukh, C N 2 

 Research Scholar, India , Amravati 
 Associate Professor, PRMIT & R Badnera 
First page
012032
Publication year
2022
Publication date
Aug 2022
Publisher
IOP Publishing
ISSN
17426588
e-ISSN
17426596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2711550892
Copyright
Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.