Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9669545 | Computer Vision and Image Understanding | 2005 | 25 Pages |
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 â¼70-80% correct discrimination performance, whereas a classifier using multiple features exceeds 90% correct discrimination.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Florin Cutzu, Riad Hammoud, Alex Leykin,