DocumentCode
1856127
Title
Image Feature Extraction and Recognition of Abstractionism and Realism Style of Indonesian Paintings
Author
Tieta Antaresti, R.P. ; Arymurthy, Aniati Murni
Author_Institution
Fac. of Comput. Sci., Univ. of Indonesia, Depok, Indonesia
fYear
2010
fDate
2-3 Dec. 2010
Firstpage
149
Lastpage
152
Abstract
This paper chooses and evaluates three feature vectors and their augmented feature vector for recognizing the styles of Indonesian paintings. The three feature extraction methods include the Gabor wavelet, histogram analysis, and number-of-edge analysis. The recognition purpose is to discriminate between the abstractionism and the realism styles of Indonesian paintings. The experimental results using 115 painting images show that the use of number-of-edge features has given the best result with 66.23% accuracy.
Keywords
art; augmented reality; edge detection; feature extraction; wavelet transforms; Gabor wavelet; Indonesian painting; abstractionism; augmented feature vector; histogram analysis; image feature extraction; image recognition; number-of-edge analysis; Feature extraction; Histograms; Image edge detection; Painting; Support vector machine classification; Testing; Canny edge detection; Gabor wavelet; Indonesian paintings; feature extraction; histogram; visual arts;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in Computing, Control and Telecommunication Technologies (ACT), 2010 Second International Conference on
Conference_Location
Jakarta
Print_ISBN
978-1-4244-8746-2
Electronic_ISBN
978-0-7695-4269-0
Type
conf
DOI
10.1109/ACT.2010.9
Filename
5675821
Link To Document