DjVu: Scanned Documents on the Web.

This page describes the design of DjVu, a document compression and imaging technology that allows the efficient online distribution of high resolution scanned documents. More information can be found on DjVu.org. You can also see the page describing DjVuLibre, a free implementation of the DjVu system. Finally, you can install the DjVu browser plugin, and view the DjVu slides.

Overview

Despite the exponential growth of the internet, most of the human knowledge is preserved on paper in the form of books, magazines, journals, … Scanning these documents offers a cost-effective way to put them online. Unfortunately high-resolution color scanned images are too large to be practical.

The main DjVu innovation is a document compression technique that reduce these high resolution image to a size comparable to that of a typical web page. For instance, DjVu needs 40KB to 60KB to represent a typical magazine page scanned in color with a resolution of 300 dpi. Such large compression ratios are possible because DjVu understands many aspects of document images.

  • The segmentation step separates a foreground image from a background image.
  • The foreground image contains the text and the line art. High compression ratios are achieved by collecting the repeated characters into a shape dictionary and simply coding the position of their occurences.
  • The background image contains the paper texture and the photographic images. High compression ratios are achieved with simple wavelets because this part of the image can be rendered with a lesser resolution.

DjVu documents can be viewed using a sophisticated browser plugin. The DjVu viewer efficiently represents high resolution images with limited memory and implements very efficient zooming and panning. The viewer automatically download the next pages in the background in order to facilitate reading. DjVu documents can be enriched with annotations and hyperlinks. They can also contain a searchable text version of the document.

Main Publications

Léon Bottou, Patrick Haffner, Paul G. Howard, Patrice Simard, Yoshua Bengio and Yann Le Cun: High Quality Document Image Compression with DjVu, Journal of Electronic Imaging, 7(3):410-425, 1998.

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Léon Bottou and Steven Pigeon: Lossy Compression of Partially Masked Still Images, Proceedings of IEEE Data Compression Conference, Snowbird, UT, April 1998.

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Léon Bottou, Paul G. Howard and Yoshua Bengio: The Z-Coder Adaptive Binary Coder, Proceedings IEEE Data Compression Conference 1998, IEEE, Snowbird, April 1998.

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Léon Bottou, Patrick Haffner and Yann Le Cun: Conversion of Digital Documents to Multilayer Raster Formats, Proceedings of the Sixth International Conference on Document Analysis and Recognition, 444-448, IEEE, Seattle, September 2001.

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Yann Le Cun, Léon Bottou, Andrei Erofeev, Patrick Haffner and Bill W. Riemers: DjVu document browsing with on-demand loading and rendering of image components, Internet Imaging, San Jose, January 2001.

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Patrick Haffner, Léon Bottou , Yann Le Cun and Luc Vincent: A General Segmentation Scheme for DjVu Document Compression, Proceedings of the International Symposium on Mathematical Morphology (ISMM'02), CSIRO publications, Sydney, Australia, April 2002.

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research/djvu.txt · Last modified: 2013/01/06 13:12 by leonb
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