Computer analysis of Van Goghs complementary colours
Traditionally, the analysis of visual arts is performed by human art experts only. The availability of advanced artificial intelligence techniques makes it possible to support art experts in their judgement of visual art. In this article currently available image-analysis techniques are applied. Our aim is (1) to determine how successful the usage of complementary colours was in the oeuvre of Vincent Van Gogh and (2) whether this characteristic may make his paintings identifiable in time. It is commonly acknowledged that, especially in his French period, Van Gogh started employing complementary colours to emphasize contours of objects or parts of scenes. This article proposes a new method called MECOCO1 to measure complementary-colour usage in a painting by combining an opponent-colour space representation with Gabor filtering. To achieve the aim, (1) we defined a novel measure called the opponency value that quantifies the usage of complementary-colour transitions in a painting and (2) we studied Van Goghs painting style. MECOCOs analysis of a dataset of 145 digitised and colour-calibrated oil-on-canvas paintings confirms the global transition pattern of complementary colours in Van Goghs paintings as generally acknowledged by art experts. In addition, MECOCO also provides an objective and quantifiable way to support the analysis of colours in individual paintings.
gabor filters image analysis color analysis automatic painting analysis opponent colors cielab space