Geometric tight frame based stylometry for art authentication of van Gogh paintings
Publication in refereed journal

香港中文大學研究人員

引用次數
替代計量分析
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其它資訊
摘要This paper is about authenticating genuine van Gogh paintings from forgeries. The paintings used in the test in this paper are provided by van Gogh Museum and Kroller-Muller Museum. The authentication process depends on two key steps: feature extraction and outlier detection. In this paper, a geometric tight frame and some simple statistics of the tight frame coefficients are used to extract features from the paintings. Then a forward stage-wise rank boosting is used to select a small set of features for more accurate classification so that van Gogh paintings are highly concentrated towards some center point while forgeries are spread out as outliers. Numerical results show that our method can achieve 86.08% classification accuracy under the leave-one-out cross-validation procedure. Our method also identifies five features that are much more predominant than other features. Using just these five features for classification, our method can give 88.61% classification accuracy which is the highest so far reported in literature. Evaluation of the five features is also performed on two hundred datasets generated by bootstrap sampling with replacement. The median and the mean are 88.61% and 87.77% respectively. Our results show that a small set of statistics of the tight frame coefficients along certain orientations can serve as discriminative features for van Gogh paintings. It is more important to look at the tail distributions of such directional coefficients than mean values and standard deviations. It reflects a highly consistent style in van Gogh's brushstroke movements, where many forgeries demonstrate a more diverse spread in these features.
著者Liu HX, Chan RH, Yao Y
會議名稱5th Tri-Annual International Conference on Computational Harmonic Analysis (ICCHA)
會議開始日19.05.2014
會議完結日23.05.2014
會議地點Nashville
期刊名稱Applied and Computational Harmonic Analysis
詳細描述In Press, Available online 2 December 2015.\n\nTo ORKTS: In Press, Available online 2 December 2015
出版年份2016
月份9
卷號41
期次2
出版社ACADEMIC PRESS INC ELSEVIER SCIENCE
頁次590 - 602
國際標準期刊號1063-5203
電子國際標準期刊號1096-603X
語言英式英語
關鍵詞Art authentication, Feature selection, Outlier detection, Stylometry, Tight frame
Web of Science 學科類別Mathematics; Mathematics, Applied; Physics; Physics, Mathematical

上次更新時間 2020-12-10 於 01:18