Who is Selling to Whom – Feature Evaluation for Multi-block Classification in Invoice Information Extraction

Warning

This publication doesn't include Faculty of Sports Studies. It includes Faculty of Informatics. Official publication website can be found on muni.cz.
Authors

HA Hien Thi HORÁK Aleš

Year of publication 2021
Type Article in Proceedings
Conference SPECOM 2021: 23rd International Conference on Speech and Computer
MU Faculty or unit

Faculty of Informatics

Citation
Web https://link.springer.com/chapter/10.1007/978-3-030-87802-3_23
Doi http://dx.doi.org/10.1007/978-3-030-87802-3_23
Keywords OCR; Invoice; Block type classification; Seller; Buyer; Delivery address
Description The invoice information extraction task aims at unifying the automatized processing of invoices in structured forms and in the form of a scanned image. Recognizing the pieces of information where a specific value is identified with a keyword (such as the invoice date) is a relatively well-managed task. On the other hand, identification of multi-block information on the invoice, such as distinguishing the seller, buyer, and the delivery address, is much more challenging due to versatile invoice layouts. In this work, we present a new technique of feature extraction and classification to recognize the seller, buyer, and delivery address text blocks in scanned invoices based on a combination of complex layout and annotated text features. The method does not only consider the block positional features but also the relation between blocks and block contents at a higher level. The technique is implemented as a module of the OCRMiner system. We offer its detailed evaluation and error analysis with a dataset of more than five hundred Czech invoices reaching the overall macro average F1-score of 94%.
Related projects:

You are running an old browser version. We recommend updating your browser to its latest version.

More info