ICDAR2019 Competition on Scanned Receipt OCR and Information Extraction

TL;DR

This paper introduces the ICDAR 2019 competition on scanned receipt OCR and information extraction, providing a new dataset, task definitions, evaluation protocols, and analysis of submitted methods to advance research in this underexplored area.

Contribution

It establishes a standardized benchmark with a new dataset and defines three specific tasks for scanned receipt OCR and information extraction, fostering progress in this field.

Findings

Created a dataset with 1000 annotated scanned receipts

Evaluated multiple methods on the defined tasks

Provided insights into current method performances

Abstract

Scanned receipts OCR and key information extraction (SROIE) represent the processeses of recognizing text from scanned receipts and extracting key texts from them and save the extracted tests to structured documents. SROIE plays critical roles for many document analysis applications and holds great commercial potentials, but very little research works and advances have been published in this area. In recognition of the technical challenges, importance and huge commercial potentials of SROIE, we organized the ICDAR 2019 competition on SROIE. In this competition, we set up three tasks, namely, Scanned Receipt Text Localisation (Task 1), Scanned Receipt OCR (Task 2) and Key Information Extraction from Scanned Receipts (Task 3). A new dataset with 1000 whole scanned receipt images and annotations is created for the competition. In this report we will presents the motivation, competition datasets, task definition, evaluation protocol, submission statistics, performance of submitted methods and results analysis.