An Automatic Reader of Identity Documents

TL;DR

This paper presents a prototype system for automatic reading and verification of Italian identity documents from photographs, aiming to replace manual processes and improve efficiency in the service industry.

Contribution

The paper introduces a novel system that localizes, classifies, and extracts data from identity documents using synthetic datasets for training and evaluation.

Findings

Effective document localization and classification from photographs

Synthetic dataset successfully used for training neural networks

System demonstrates promising performance in data extraction

Abstract

Identity documents automatic reading and verification is an appealing technology for nowadays service industry, since this task is still mostly performed manually, leading to waste of economic and time resources. In this paper the prototype of a novel automatic reading system of identity documents is presented. The system has been thought to extract data of the main Italian identity documents from photographs of acceptable quality, like those usually required to online subscribers of various services. The document is first localized inside the photo, and then classified; finally, text recognition is executed. A synthetic dataset has been used, both for neural networks training, and for performance evaluation of the system. The synthetic dataset avoided privacy issues linked to the use of real photos of real documents, which will be used, instead, for future developments of the system.