Classifying images on the web automatically
作者： Rainer Lienhart , Alexander Hartmann
DOI: 10.1117/1.1502259
关键词:
摘要: Numerous research works about the extraction of low-level features from images and videos have been published. However, only recently focus has shifted to exploiting classify automatically into semantically broad meaningful categories. In this paper, novel classification algorithms are presented for three general-purpose detail, we present distinguishing photo-like graphical images, actual photos photo-like, but artificial presentation slides/scientific posters comics. On a large image database, our algorithm achieved an accuracy 97.69% in separating images. subset true could be separated ray-traced/rendered with 97.3%, while 99.5% was successfully partitioned
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