Optical Character Recognition (OCR) Using Opencv and Python

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.