A Review on OCR Technology
Jay Dilipbhai Thanki, Priyank Dineshbhai Davda, Priya R. Swaminarayan · Journal of Emerging Technologies and Innovative Research · 2021
Optical Character Recognition (OCR), is that the process of conversion of image text or handwritten text into machine understandable form. Simply OCR means conversion of characters that is recognized and convert it into computer readable form. It is widely used as a kind of data entry from original paper data sources such as banking papers or consultation papers, whether passport documents, invoices, statement, receipts, card, mail or any number of printed records. It is a standard method of digitizing printed texts in order that they will be electronically edited, searched, and stored more compactly. OCR is the field of research in Pattern Recognition, Artificial Intelligence and Computer Vision. OCR is that the electronic translation of handwritten, type written or printed text into machine translated images. It is widely used to recognize and search text from documents or to publish the text on a website. This document represents review of Optical Character Recognition methods such as Correlation of Character Recognition, Pre-Processing, Segmentation, Neural Network and Structural Components Extraction and discuss their advantages and disadvantages. Through Neural Network method, Optical Character Recognition typing error can be solved which may increase the efficiency of conversion rate. This paper represents all the techniques and algorithms that is used to find accurate results for OCR.