OCR Using Python and Its Application

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Sumita Mukherjee
Hritik Tyagi
Purushautam Tyagi
Nikita Singh
Shraddha Bhardwaj

Abstract

Optical Character Recognition (OCR) of papers has tremendous practical value given the prevalence of handwritten documents in human exchanges. A discipline known as optical character recognition makes it possible to convert many kinds of texts or photos into editable, searchable, and analysable data. In the past ten years, academics have developed systems that automatically evaluate printed and handwritten documents to convert them to electronic format. In the modern era, as demand for computer systems arose, the demand to convert paper text and computer vision also erose. To interact the computer with capability to read text from images, videos and images have been arose rapidly and many software companies came in role to fulfil this need. One of the active and difficult study areas in the world of pattern recognition and image processing has been handwriting recognition. Among its many uses are bank checks, reading assistance for the blind, and the conversion of any handwritten document into structural text. The main aim of this paper is to create a searchable pdf from the image and bring the application to easy use and deployable on premises and cloud.


 

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How to Cite
Mukherjee, S. ., Tyagi, H. ., Tyagi, P. ., Singh, N. ., & Bhardwaj, S. . (2023). OCR Using Python and Its Application. Journal of Advanced Zoology, 44(S3), 1083–1092. https://doi.org/10.17762/jaz.v44iS-3.1062
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