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JEI
2002

Classifying images on the web automatically

13 years 3 months ago
Classifying images on the web automatically
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 generalpurpose 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 poser...
Rainer Lienhart, Alexander Hartmann
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Where JEI
Authors Rainer Lienhart, Alexander Hartmann
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