AIMar 18, 2021

ICDAR2019 Competition on Scanned Receipt OCR and Information Extraction

arXiv:2103.10213v1416 citations
Originality Synthesis-oriented
AI Analysis

This work provides a benchmark for document analysis in commercial applications, but it is incremental as it focuses on competition organization rather than novel method development.

The paper organized the ICDAR 2019 competition to address the lack of research in scanned receipt OCR and information extraction (SROIE), setting up three tasks and creating a new dataset of 1000 annotated receipt images to benchmark methods.

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.

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