Image feature extraction and recognition of abstractionism and realism style of Indonesian paintings

R. P. Tieta Antaresti, Aniati Murni Arymurthy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 2010 2nd International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2010
Pages149-152
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2010
Event2010 2nd International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2010 - Jakarta, Indonesia
Duration: 2 Dec 20103 Dec 2010

Publication series

NameProceedings - 2010 2nd International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2010

Conference

Conference2010 2nd International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2010
Country/TerritoryIndonesia
CityJakarta
Period2/12/103/12/10

Keywords

  • Canny edge detection
  • Feature extraction
  • Gabor wavelet
  • Histogram
  • Indonesian paintings
  • Visual arts

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