• 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