Distinguishing paintings from photographs

Authors:
Florin Cutzu;Riad Hammoud;Alex Leykin
Affiliations:
Department of Computer Science, Indiana University, Bloomington, IN 47405, USA;Department of Computer Science, Indiana University, Bloomington, IN 47405, USA;Department of Computer Science, Indiana University, Bloomington, IN 47405, USA
Venue:
Computer Vision and Image Understanding
Year:
2005

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Abstract

We addressed the problem of automatically differentiating photographs of real scenes from photographs of paintings. We found that photographs differ from paintings in their color, edge, and texture properties. Based on these features, we trained and tested a classifier on a database of 6000 paintings and 6000 photographs. Using single features results in ~70-80% correct discrimination performance, whereas a classifier using multiple features exceeds 90% correct discrimination.