  What is the creative process through which an artist goes from an original
image to a painting? Can we examine this process using techniques from computer
vision and pattern recognition? Here we set the first preliminary steps to
algorithmically deconstruct some of the transformations that an artist applies
to an original image in order to establish centres of interest, which are focal
areas of a painting that carry meaning. We introduce a comparative methodology
that first cuts out the minimal segment from the original image on which the
painting is based, then aligns the painting with this source, investigates
micro-differences to identify centres of interest and attempts to understand
their role. In this paper we focus exclusively on micro-differences with
respect to edges. We believe that research into where and how artists create
centres of interest in paintings is valuable for curators, art historians,
viewers, and art educators, and might even help artists to understand and
refine their own artistic method.
