A Survey of Optical Character Recognition Techniques on Indic Script
Ramya Chirimilla, Vishnu Vardhan B · ECS Transactions · 2022
Optical Character Recognition (OCR) is a technique that converts printed text and images into a digitized form, which can be manipulated by a machine. It has many application sectors like Banking, Financial, Legal applications, etc. Initially researchers were addressed and proposed many algorithms in image processing for character recognition and mapping. Most of the researchers focused on the Latin script English as it was supported by the Encoding standard ASCII. Later, people start realizing that OCR techniques for other languages are also gaining momentum these days. With the advent of technology and Unicode revolution, native language-based OCR solutions started emerging. In this paper, we aim to focus on the latest machine learning techniques applied on OCR for the language English and two languages from Indian continent were presented. Out of the two Indian languages, one is the stroke-based language, i.e. Hindi, and the other being cursive script-based language Telugu.