DocumentCode :
3642755
Title :
Classification of art paintings by genre
Author :
Mateja Čuljak;Bruno Mikuš;Karlo Jež;Stjepan Hadjić
Author_Institution :
Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia
fYear :
2011
fDate :
5/1/2011 12:00:00 AM
Firstpage :
1634
Lastpage :
1639
Abstract :
This paper offers an approach to automatic art genre classification of paintings. Development of machine learning algorithms and increase of overall computing power improved speed and efficiency of feature extraction from digital images and with it opened a whole new set of possibilities in classification of visual data such as paintings and other visual art. Automatic classification is useful in large database processing (e.g. museums) and could be used as a commercial application on mobile platforms. Six genres are classified in the paper: realism, impressionism, cubism, fauvism, pointilism and naïve art. Some of the genres have now been tested for the first time. Used features are described as well as a measure of their usefulness. Rate of success for different classifiers is given. Accomplished results are similar to related work results.
Keywords :
"Image color analysis","Art","Painting","Histograms","Image edge detection","Feature extraction","Pixel"
Publisher :
ieee
Conference_Titel :
MIPRO, 2011 Proceedings of the 34th International Convention
Print_ISBN :
978-1-4577-0996-8
Type :
conf
Filename :
5967323
Link To Document :
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