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Volume: 1 | Article ID: art00085
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Digital Documents Classification for Optimized Processing and Rendering
R. Schettini
C. Brambilla
A. Valsasna
M.De Ponti
  DOI :  10.2352/CGIV.2002.1.1.art00085  Published Online :  January 2002
Abstract

The problem addressed in this paper is the high-level problem of distinguishing among photographs, graphics, texts and compound documents. To cope with the great variety of compound documents we have designed a hierarchical classification strategy which first classifies images as compound or not-compound by verifying the homogeneity of the sub-images in terms of low-level features. Not-compound images are then classified as photographs, graphics or texts. Results of our experiments on a database of over 35000 images collected from various sources will be reported and discussed in the final paper.

Journal Title : Conference on Colour in Graphics, Imaging, and Vision
Publisher Name : Society of Imaging Science and Technology
Publisher Location : 7003 Kilworth Lane, Springfield, VA 22151, USA
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 DOI 10.2352/CGIV.2002.1.1.art00085
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R. Schettini, C. Brambilla, A. Valsasna, M.De Ponti, "Digital Documents Classification for Optimized Processing and Rendering"  in Proc. IS&T CGIV 2002 First European Conf. on Colour in Graphics, Imaging, and Vision,  2002,  pp 402 - 405,  https://doi.org/10.2352/CGIV.2002.1.1.art00085

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Copyright © Society for Imaging Science and Technology 2002
72010351
Conference on Colour in Graphics, Imaging, and Vision
conf colour graph imag vis
2158-6330
Society of Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151, USA
2158-6330(20020101)2002:1L.402;1-
cgiv_v2002n1/splitsection85.xml
/ist/cgiv/2002/00002002/00000001/art00085
Articles
Digital Documents Classification for Optimized Processing and Rendering
SchettiniR.
BrambillaC.
ValsasnaA.
PontiM.De
01012002
2002
1
402
405
2002
The problem addressed in this paper is the high-level problem of distinguishing among photographs, graphics, texts and compound documents. To cope with the great variety of compound documents we have designed a hierarchical classification strategy which first classifies images as compound or not-compound by verifying the homogeneity of the sub-images in terms of low-level features. Not-compound images are then classified as photographs, graphics or texts. Results of our experiments on a database of over 35000 images collected from various sources will be reported and discussed in the final paper.