Identifying painters from color profiles of skin patches in painting images

Research on digital analysis of painting images has received very little attention. The exact nature of scientific methods seems to be antithesis of art. Nevertheless, several papers have proposed methods to bridge this gap and have obtained interesting results. In fact, some art theorists have pointed out the usefulness of specific quantization features in the paintings. This paper presents a method for identifying painters using color profiles of skin patches in painting images. Various color models for representing the color profiles were explored. Various implementations of multi-class Support Vector Machine classifiers were compared. We found that a weighted combination of several Directed Acyclic Graph SVMs with Gaussian kernels gives the best classification performance.