Computer-assisted analysis of painting brushstrokes: Digital image processing for unsupervised extraction of visible features from van Gogh's works

The automatic extraction of objective features from paintings, like brushstrokes distribution, orientation and shape, could be particularly useful for different artwork analysis and management tasks. In fact, these features contribute to provide a unique signature of the artists' style and can be effectively used for artist identification and classification, artwork examination and retrieval, etc. In this paper, an automatic technique for unsupervised extraction of individual brushstrokes from digital reproductions of van Gogh's paintings is presented. Through the iterative application of segmentation, characterization and validation steps, valid brushstrokes complying with specific area and shape constraints are identified. On the extracted brushstrokes, several representative features can then be calculated, like orientation, length and width. The accuracy of the devised method is evaluated by comparing numerical results obtained on a dataset of digital reproductions of van Gogh's oil-on-canvas works with observations made by human subjects and with another recent approach for automatic brushstrokes analysis. Experimental tests showed that the devised methodology produces results that are rather close to those obtained by human subjects and, for some of the metrics considered, can provide improved performances with respect to alternative technique