An End-to-End Optical Character Recognition Pipeline for Indonesian Identity Card

Abstract

Optical Character Recognition has been long studied over the past few years. The challenge remains for the specific purpose of extracting information from image documents. The aim of this study is to create an end-to-end pipeline for an Indonesian identity card. The final pipeline uses deep learning approach consist of Faster R-CNN for text detection, YOLOv5 for character detection, and Support Vector Machine for Character Recognition. The proposed pipeline showed a remarkable result for both the identity number and the full name. This provides a powerful tool for the auto-fill form and verification process effectively and efficiently.