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Optical Character Recognition (OCR) Using Opencv and Python: Implementation and Performance Analysis
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Author(s): A. V. Senthil Kumar (Hindusthan College of Arts and Science, India), Ajay Karthick M. (Hindusthan College of Arts and Science, India), Ahmad Fuad Hamadah Bader (Jadara Universty, Jordan), Gaganpreet Kaur (Chitkara University, India), Samrat Ray (Peter the Great Saint Petersburg Polytechnic University, Russia), Prasanna Lakshmi G. (Sandip University, India), Paresh Virparia (Sardar Patel University, India), Bharat Bhushan Sagar (Harcourt Butler Technical University, India), Amit Dutta (All India Council for Technical Education, India), Shadi R. Masadeh (Isra University, Jordan), Uma N. Dulhare (Muffakham Jah College of Engineering and Technology, India)and Asadi Srinivasulu (University of Newcastle, Australia)
Copyright: 2024
Pages: 17
Source title:
Hyperautomation in Business and Society
Source Author(s)/Editor(s): Dina Darwish (Ahram Canadian University, Egypt)
DOI: 10.4018/979-8-3693-3354-9.ch008
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Abstract
Optical character recognition (OCR) stands as a transformative technology at the intersection of computer vision and document processing. This chapter explores the advancements and challenges in OCR, focusing on methods for extracting text content from images, scanned documents, and other visual media. The review encompasses traditional techniques, such as template matching and feature-based methods, as well as state-of-the-art deep learning approaches. The evolution of OCR algorithms is discussed in the context of their applications in digitizing historical archives, automating data entry, enhancing accessibility, and facilitating language translation. Additionally, attention is given to challenges related to diverse fonts, handwriting recognition, and handling complex document layouts. The chapter concludes with an outlook on emerging trends and future directions in OCR research, emphasizing the ongoing pursuit of accuracy, robustness, and efficiency in extracting textual information from visual data.
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