SPECIAL SECTION ON INTERNET IMAGING

Classifying images on the web automatically

[+] Author Affiliations
Rainer Lienhart, Alexander Hartmann

Intel Labs, Intel Corporation, 2200 Mission College Boulevard, Santa Clara, California?95052-8119 E-mail: rainer.lienhart@intel.com

J. Electron. Imaging. 11(4), 445-454 (Oct 01, 2002). doi:10.1117/1.1502259
History: Received Feb. 18, 2002; Revised May 31, 2002; Accepted Jun. 12, 2002; Online October 15, 2002
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Numerous research works about the extraction of low-level features from images and videos have been published. However, only recently the focus has shifted to exploiting low-level features to classify images and videos automatically into semantically broad and meaningful categories. In this paper, novel classification algorithms are presented for three broad and general-purpose categories. In detail, we present algorithms for distinguishing photo-like images from graphical images, actual photos from only photo-like, but artificial images and presentation slides/scientific posters from comics. On a large image database, our classification algorithm achieved an accuracy of 97.69% in separating photo-like images from graphical images. In the subset of photo-like images, true photos could be separated from ray-traced/rendered image with an accuracy of 97.3%, while with an accuracy of 99.5% the subset of graphical images was successfully partitioned into presentation slides/scientific posters and comics. © 2002 SPIE and IS&T.

© 2002 SPIE and IS&T

Citation

Rainer Lienhart and Alexander Hartmann
"Classifying images on the web automatically", J. Electron. Imaging. 11(4), 445-454 (Oct 01, 2002). ; http://dx.doi.org/10.1117/1.1502259


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