APPLICATION OF ZONAL AND CURVATURE FEATURES TO NUMERALS RECOGNITION

International Journal of Students' Research in Technology & Management

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Field Value
 
Title APPLICATION OF ZONAL AND CURVATURE FEATURES TO NUMERALS RECOGNITION
 
Creator Kumar Prasad, Binod
 
Subject Curvature Features
Zonal Features
Numeral Recognition
Delta Distance Coding
Slope Features
Curvature Features
 
Description Purpose of the study: The purpose of this work is to present an offline Optical Character Recognition system to recognise handwritten English numerals to help automation of document reading. It helps to avoid tedious and time-consuming manual typing to key in important information in a computer system to preserve it for a longer time.
Methodology: This work applies Curvature Features of English numeral images by encoding them in terms of distance and slope. The finer local details of images have been extracted by using Zonal features. The feature vectors obtained from the combination of these features have been fed to the KNN classifier. The whole work has been executed using the MatLab Image Processing toolbox.
Main Findings: The system produces an average recognition rate of 96.67% with K=1 whereas, with K=3, the rate increased to 97% with corresponding errors of 3.33% and 3% respectively. Out of all the ten numerals, some numerals like ‘3’ and ‘8’ have shown respectively lower recognition rates. It is because of the similarity between their structures.
Applications of this study: The proposed work is related to the recognition of English numerals. The model can be used widely for recognition of any pattern like signature verification, face recognition, character or word recognition in another language under Natural Language Processing, etc.
Novelty/Originality of this study: The novelty of the work lies in the process of feature extraction. Curves present in the structure of a numeral sample have been encoded based on distance and slope thereby presenting Distance features and Slope features. Vertical Delta Distance Coding (VDDC) and Horizontal Delta Distance Coding (HDDC) encode a curve from vertical and horizontal directions to reveal concavity and convexity from different angles.
 
Publisher GIAP Journals
 
Date 2021-04-13
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier https://giapjournals.com/ijsrtm/article/view/ijsrtm.2021.922
10.18510/ijsrtm.2021.922
 
Source International Journal of Students' Research in Technology & Management; Vol. 9 No. 2 (2021); 7-12
2321-2543
 
Language eng
 
Relation https://giapjournals.com/ijsrtm/article/view/ijsrtm.2021.922/3419
 
Rights Copyright (c) 2021 Prasad
https://creativecommons.org/licenses/by-sa/4.0
 

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