Online template matching over a stream of digitized documents

Abstract

Although living in the information age for decades, paperwork is still a tedious part of everybody's life. Assistance systems that implement techniques of digitization and document understanding may offer considerable reductions in time and effort for the users. A large portion of paper documents like invoices, delivery receipts or admonitions are based on a fixed company specific template and therefore exhibit a high degree of similarity. In this work, we propose a template extraction method over a stream of incoming documents and a template allocation method for assigning new instances from the stream to the most suitable templates. Our method employs text augmented by layout information to represent the digital image of the paper document. Document similarity is assessed with respect to both textual and layout parts of the document; the matching terms contribute accordingly to their distance to the query terms. To be more robust against distortions on the documents due to the digitization process, the templates are not static, rather they are maintained in an online fashion based on their new assigned documents. Real data experiments show that the combination of textual and layout information and the continuous template adaptation through online update, improves the template identification quality of earlier proposed methods.