DocumentCode :
582221
Title :
Scientific understanding of visual art
Author :
Yi, Zhang ; Yuanyuan, Pu ; Dan, Xu
Author_Institution :
Sch. of Inf. & Eng., Yunnan Univ., Kunming, China
fYear :
2012
fDate :
25-27 July 2012
Firstpage :
3922
Lastpage :
3927
Abstract :
The authentication and classification of Visual arts used to be depended on the judgment of the artist himself according to experience and knowledge of the artwork and its artist. Recently, the development of computer and image processing technology has made the processing of digital visual artworks possible. More and more museums and libraries have their collections to be digitalized, which make the study of problems haunted the art historians based on these digital images available. In this paper, the research of understanding of visual arts based on computer and low-level information of paintings, which can be called scientific understanding of visual arts, has been brought out. Some features, including multi-scale amplitude, distribution of coefficients of Curvelets and non-stationary of artworks, are extracted to evaluate the style of different artist and some other respects of the artwork. The relations between the style of visual arts and these features are also stated. It is apparent that each feature reflects different characteristics of the painting technique.
Keywords :
art; curvelet transforms; feature extraction; image classification; museums; artwork nonstationary coefficient distribution; computer technology; curvelet coefficient distribution; curvelet transform; digital visual artworks; image processing technology; multiscale amplitude; painting technique; scientific understanding; style extraction; visual art authentication; visual art classification; Abstracts; Art; Computers; Educational institutions; Feature extraction; Painting; Visualization; Computational esthetics; Curvelet transform; Scientific understanding; Style; Visual art;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
ISSN :
1934-1768
Print_ISBN :
978-1-4673-2581-3
Type :
conf
Filename :
6390611
Link To Document :
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