Optical Character Recognition based on Template Matching

Article ID

CSTSDE4951M

Optical Character Recognition based on Template Matching

Md. Anwar Hossain
Md. Anwar Hossain
Sadia Afrin
Sadia Afrin
DOI

Abstract

This paper presents an innovative design for Optical Character Recognition (OCR) from text images by using the Template Matching method.OCR is an important research area and one of the most successful applications of technology in the field of pattern recognition and artificial intelligence.OCR provides full alphanumeric visualization of printed and handwritten characters by scanning text images and converts it into a corresponding editable text document. The main objective of this system prototype is to develop a prototype for the OCR system and to implement The Template Matching algorithm for provoking the system prototype. In this paper, we took alphabet (A-Z and a-z), and numbers (0-1), grayscale images, bitmap image format were used and recognized the alphabet and numbers by comparing between two images. Besides, we checked accuracy for different fonts of alphabet and numbers. Here we used Matlab R2018a software for the proper implementation of the system.

Optical Character Recognition based on Template Matching

This paper presents an innovative design for Optical Character Recognition (OCR) from text images by using the Template Matching method.OCR is an important research area and one of the most successful applications of technology in the field of pattern recognition and artificial intelligence.OCR provides full alphanumeric visualization of printed and handwritten characters by scanning text images and converts it into a corresponding editable text document. The main objective of this system prototype is to develop a prototype for the OCR system and to implement The Template Matching algorithm for provoking the system prototype. In this paper, we took alphabet (A-Z and a-z), and numbers (0-1), grayscale images, bitmap image format were used and recognized the alphabet and numbers by comparing between two images. Besides, we checked accuracy for different fonts of alphabet and numbers. Here we used Matlab R2018a software for the proper implementation of the system.

Md. Anwar Hossain
Md. Anwar Hossain
Sadia Afrin
Sadia Afrin

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Md. Anwar Hossain. 2019. “. Global Journal of Computer Science and Technology – C: Software & Data Engineering GJCST-C Volume 19 (GJCST Volume 19 Issue C2): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Issue Cover
GJCST Volume 19 Issue C2
Pg. 31- 35
Classification
GJCST-C Classification: I.2.7
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Optical Character Recognition based on Template Matching

Md. Anwar Hossain
Md. Anwar Hossain
Sadia Afrin
Sadia Afrin

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