Illustrated Book Study: Digital Conversion Requirements of Printed Illustrations

  • Anne R. Kenney
  • Louis H. SharpeII
  • Barbara Berger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1513)


Cornell University Department of Preservation and Conservation and Picture Elements, Incorporated have undertaken a joint study for the Library of Congress to determine the best means for digitizing the vast array of illustrations used in 19th and early 20th century publications. This work builds on two previous studies. A Cornell study [1] characterized a given illustration type based upon its essence, detail, and structure. A Picture Elements study [2] created guidelines for deciding how a given physical content region type should be captured as an electronic content type. Using those procedures, appropriate mappings of different physical content regions (representing instances of different illustration processes) to electronic content types are being created. These mappings differ based on the illustration type and on the need to preserve information at the essence, detail, or structure level. Example pages that are typical of early commercial illustrations have been identified, characterized in terms of the processes used to create them (e.g., engraving, lithograph, halftone) and then scanned at high resolutions in 8-bit grayscale. Digital versions that retain evidence of information at the structure level have been derived from those scans and their fidelity studied alongside the paper originals. Project staff have investigated the available means for automatic detection of illustration content regions and methods for automatically discriminating different illustration process types and for encoding and processing them. A public domain example utility is being created which automatically detects the presence and location of a halftone region in a scan of an illustrated book page and applies special processing to it.


Electronic Image Picture Element Separate Plate Text Page Tonal Variation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Anne R. Kenney
    • 1
  • Louis H. SharpeII
    • 1
  • Barbara Berger
    • 1
  1. 1.Cornell University Library and Picture Elements, Inc.USA

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