QUANTRIUM GUIDES

Integrating multiple OCR models to perform detection and recognition separately using Python

Image data extraction using Python

Introduction

Optical Character Recognition (OCR) is one of the most challenging problems in Computer Vision today. With reduced hardware cost of handheld devices like mobile phones and having very high quality of cameras, it has largely replaced the scanners for normal use. Even, mobile applications provide options to click image of the documents and upload, for example, loan application, bank account opening, scanning of old manuscripts and books, etc.

Hence, images of documents have become one of the most widely used source of data. The text extraction from these images is largely dependent on the OCR.

Some of the important applications of OCR include:

• Text extraction from scanned or captured documents;
• License plate detection and recognition;
• Handwritten text recognition;

and the list goes on. Thus, it is essential to build/design a robust OCR model that detects the text present in the images with high accuracy.