Optimized CNN-Based Recognition of District Names of Punjab State in Gurmukhi Script

Automation of Postal systems has the major research scope in the field of automation. To create Postal Automation set-up for countries like India is a tedious task if compared with other countries because of India’s multiscript and multilingual behavior. This work will help in recognizing the “Gurmu...

Full description

Saved in:
Bibliographic Details
Main Authors: Sandhya Sharma, Sheifali Gupta, Deepali Gupta, Sapna Juneja, Hamza Turabieh, Lokesh Sharma, Zelalem Kiros Bitsue
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2022/6580839
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Automation of Postal systems has the major research scope in the field of automation. To create Postal Automation set-up for countries like India is a tedious task if compared with other countries because of India’s multiscript and multilingual behavior. This work will help in recognizing the “Gurmukhi” handwritten district names of the State Punjab. To recognize the district names, a CNN-based architecture is proposed by employing a Holistic approach. For this, an image database of 22000 samples is prepared having 1000 sample images for every district name which is collected from 500 different writers. Maximum accuracy on validation data achieved by the proposed Model is 99%.
ISSN:2314-4785