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Optical Engineering • Open Access

Style-based classification of Chinese ink and wash paintings
Author(s): Jiachuan Sheng; Jianmin Jiang

Paper Abstract

Following the fact that a large collection of ink and wash paintings (IWP) is being digitized and made available on the Internet, their automated content description, analysis, and management are attracting attention across research communities. While existing research in relevant areas is primarily focused on image processing approaches, a style-based algorithm is proposed to classify IWPs automatically by their authors. As IWPs do not have colors or even tones, the proposed algorithm applies edge detection to locate the local region and detect painting strokes to enable histogram-based feature extraction and capture of important cues to reflect the styles of different artists. Such features are then applied to drive a number of neural networks in parallel to complete the classification, and an information entropy balanced fusion is proposed to make an integrated decision for the multiple neural network classification results in which the entropy is used as a pointer to combine the global and local features. Evaluations via experiments support that the proposed algorithm achieves good performances, providing excellent potential for computerized analysis and management of IWPs.

Paper Details

Date Published: 3 September 2013
PDF: 9 pages
Opt. Eng. 52(9) 093101 doi: 10.1117/1.OE.52.9.093101
Published in: Optical Engineering Volume 52, Issue 9
Show Author Affiliations
Jiachuan Sheng, Tianjin Univ. of Finance and Economics (China)
Jianmin Jiang, Tianjin Univ. (China)


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