OpenPSS: An Open Page Stream Segmentation Benchmark

Ruben van Heusden, Jaap Kamps, Maarten Marx

Abstract: In recent years, an increasing number of companies and institutions have begun the process of digitizing their physical records to promote digital access and searchability of their collections. For cost-efficiency, documents are often scanned in consecutively, resulting in large PDF files consisting of many documents. Although cost-effective, this practice can be harmful for searchability when these concatenated documents are used to build a search engine. The task of Page Stream Segmentation is concerned with recovering the original document boundaries through the analysis of the text and/or images of these PDF files. Currently, many of the approaches to solving this problem make use of machine learning techniques that require significant amounts of training data. However, due to the sometimes sensitive nature of the data, few large datasets exist, and there is a lack of agreed-upon metrics to measure system performance.