Title :
Classifying traditional Chinese painting images
Author :
Jiang, Shuqiang ; Gao, Wen ; Wang, Weiqiang
Author_Institution :
Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing, China
Abstract :
More and more traditional Chinese painting art images are digitalized and exhibited on the Internet. Effective browsing and retrieving them is an imperative problem need to be addressed. This paper proposes a scheme to classify traditional Chinese paintings. The algorithm uses three low-level features to achieve such a high-level classification: Ohta histogram, color coherence vector and auto-correlation. An accuracy of 97.21% was achieved on the database of 1254 Chinese painting database.
Keywords :
Internet; art; image classification; image retrieval; visual databases; Chinese painting images; Internet; Ohta histogram; auto-correlation; browsing; color coherence vector; digitalized images; high-level classification; low-level features; painting database; retrieving; Art; Histograms; Image databases; Image retrieval; Internet; Painting; Spatial databases; Support vector machine classification; Support vector machines; Testing;
Conference_Titel :
Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Conference of the Fourth International Conference on
Print_ISBN :
0-7803-8185-8
DOI :
10.1109/ICICS.2003.1292780
