Open AccessCustom OCR for Identity Documents:OCRXNet
Author(s) -
Kawal Arora,
Ankur Singh Bist,
Roshan Prakash,
Saksham Chaurasia
Publication year - 2020
Publication title -
aptisi transactions on technopreneurship
Language(s) - English
Resource type - Journals
eISSN - 2656-8888
pISSN - 2655-8807
DOI - 10.34306/att.v2i2.87
Subject(s) - optical character recognition , pipeline (software) , computer science , identity (music) , artificial intelligence , process (computing) , information retrieval , character recognition , natural language processing , image (mathematics) , pattern recognition (psychology) , programming language , physics , acoustics
Recent advancements in the area of Optical Character Recognition (OCR) using deep learning techniques made it possible to use for real world applications with good accuracy. In this paper we present a system named as OCRXNet. OCRXNetv1, OCRXNetv2 and OCRXNetv3 are proposed and compared on different identity documents. Image processing methods and various text detectors have been used to identify best fitted process for custom ocr of identity documents. We also introduced the end to end pipeline to implement OCR for various use cases.