Geometric Tight Frame based Stylometry for Art Authentication of van Gogh Paintings

TL;DR

This paper introduces a geometric tight frame-based method for authenticating van Gogh paintings, achieving high classification accuracy by selecting key features that capture the artist's consistent brushstroke style.

Contribution

The paper presents a novel feature extraction and selection approach using geometric tight frames and rank boosting for art authentication, outperforming previous methods.

Findings

Achieves 86.08% classification accuracy with all features.

Identifies five dominant features that improve accuracy to 88.61%.

Demonstrates the importance of tail distribution features over mean values.

Abstract

This paper is about authenticating genuine van Gogh paintings from forgeries. 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.