Extensible System for Optical Character Recognition of Maintenance Documents
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John Anthony Labarga, Amardeep Singh, Vera Zaychik Moffitt
2018 Volume 10
Abstract
In the course of maintenance and operations, equipment operators and manufacturers frequently generate large volumes of paper documents. This is particularly the case in maintaining legacy systems, and when external factors (e.g. security concerns, environment, training procedures) make it infeasible to record data in a computer system in real time. To implement analytics or automated monitoring, these documents must later be converted to digital copies, which can be ingested into a database. This paper describes a flexible system for converting paper forms into digital documents through Optical Character Recognition (OCR), utilizing open source tools and packages. This system allows for the incorporation of business rules and processes that deliver high fidelity digital copies.
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Date 2018-09-24
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