Share Email Print

Proceedings Paper

The Lehigh Steel Collection: a new open dataset for document recognition research
Author(s): Barri Bruno; Daniel Lopresti
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Document image analysis is a data-driven discipline. For a number of years, research was focused on small, homogeneous datasets such as the University of Washington corpus of scanned journal pages. More recently, library digitization efforts have raised many interesting problems with respect to historical documents and their recognition. In this paper, we present the Lehigh Steel Collection (LSC), a new open dataset we are currently assembling which will be, in many ways, unique to the field. LSC is an extremely large, heterogeneous set of documents dating from the 1960's through the 1990's relating to the wide-ranging research activities of Bethlehem Steel, a now-bankrupt company that was once the second-largest steel producer and the largest shipbuilder in the United States. As a result of the bankruptcy process and the disposition of the company's assets, an enormous quantity of documents (we estimate hundreds of thousands of pages) were left abandoned in buildings recently acquired by Lehigh University. Rather than see this history destroyed, we stepped in to preserve a portion of the collection via digitization. Here we provide an overview of LSC, including our efforts to collect and scan the documents, a preliminary characterization of what the collection contains, and our plans to make this data available to the research community for non-commercial purposes.

Paper Details

Date Published: 24 March 2014
PDF: 9 pages
Proc. SPIE 9021, Document Recognition and Retrieval XXI, 90210O (24 March 2014); doi: 10.1117/12.2042615
Show Author Affiliations
Barri Bruno, Lehigh Univ. (United States)
Daniel Lopresti, Lehigh Univ. (United States)

Published in SPIE Proceedings Vol. 9021:
Document Recognition and Retrieval XXI
Bertrand Coüasnon; Eric K. Ringger, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?