Custom OCR for Identity Documents:OCRXNet
| Autor: | Saksham Chaurasia, Ankur Singh Bist, Kawal Arora, Roshan Prakash |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Information retrieval
Process (engineering) business.industry Computer science Text Detector Tesseract Yolo CRAFT Noise Removal Deep learning General Engineering Image processing Optical character recognition computer.software_genre Pipeline (software) ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Identity (object-oriented programming) General Earth and Planetary Sciences Use case Tesseract Artificial intelligence business computer General Environmental Science |
| Zdroj: | Aptisi Transactions on Technopreneurship (ATT); Vol. 2 No. 2 (2020): September; 112-119 Aptisi Transactions On Technopreneurship (ATT); Vol 2 No 2 (2020): September; 112-119 |
| ISSN: | 2656-8888 2655-8807 |
| DOI: | 10.34306/att.v2i2.87 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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