DATA EXTRACTION USING DOCUMENT UNDERSTANDING USING RPA

Abstract

Data Extraction using Document Understanding (DEDU) represent the processes of recognizing text from scanned receipts and extracting key texts from them and save the extracted tests to structured documents. DEDU 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 DEDU, we organized the ICDAR 2019 competition on DEDU. In this competition, we set up three tasks, namely, Scanned Receipt Text Localization (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. The competition opened on 10th February, 2019 and closed on 5th May, 2019. There are 29, 24 and 18 valid submissions received for the three competition tasks, respectively. In this report we will presents the motivation, competition datasets, task definition,evaluation protocol, submission statistics, performance of submitted methods and results analysis.