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