Indonesian ID Card Extractor Using Optical Character Recognition and Natural Language Post-Processing

TL;DR

This paper presents an Indonesian ID card extraction system combining OCR and NLP to improve data accuracy, achieving an F-score of 0.78 and processing each card in under five seconds.

Contribution

It introduces a novel integration of OCR and NLP techniques specifically for Indonesian ID cards to enhance extraction accuracy and processing speed.

Findings

Achieved 0.78 F-score in ID card text extraction

Processed each ID card in approximately 4510 milliseconds

Demonstrated improved accuracy with NLP text correction

Abstract

The development of Information Technology has been increasingly changing the means of information exchange leading to the need of digitizing print documents. In the present era, there is a lot of fraud that often occur. To avoid account fraud there was verification using ID card extraction using OCR and NLP. Optical Character Recognition (OCR) is technology that used to generate text from image. With OCR we can extract Indonesian ID card or kartu tanda penduduk (KTP) into text too. This is using to make easier service operator to do data entry. To improve the accuracy we made text correction using Natural language Processing (NLP) method to fixing the text. With 50 Indonesian ID card image we got 0.78 F-score, and we need 4510 milliseconds to extract per ID card.