Automatic classification of images on the Web

Alexander Hartmann; Rainer W. Lienhart

doi:10.1117/12.451108

19 December 2001 Automatic classification of images on the Web

Alexander Hartmann, Rainer W. Lienhart

Proceedings Volume 4676, Storage and Retrieval for Media Databases 2002; (2001) https://doi.org/10.1117/12.451108
Event: Electronic Imaging, 2002, San Jose, California, United States

Abstract

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 meaningful and broad 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, true photos from only photo-like, but artificial images and presentation slides from comics. On a large image database, our classification algorithm achieved an accuracy of 97.3% 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 87.3%, while with an accuracy of 93.2% the subset of graphical images was successfully partitioned into presentation slides and comics.

Citation Download Citation

Alexander Hartmann and Rainer W. Lienhart "Automatic classification of images on the Web", Proc. SPIE 4676, Storage and Retrieval for Media Databases 2002, (19 December 2001); https://doi.org/10.1117/12.451108

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