Identifying centres of interest in paintings using alignment and edge detection: Case studies on works by Luc Tuymans
This research provides a new algorithmic approach for art historians, curators, viewers, and educators to analyze the creative process of artists by identifying centers of interest in paintings.
This paper introduces a comparative methodology to identify centers of interest in paintings by analyzing micro-differences in edges between a painting and its original source image. The method involves cutting out the minimal segment from the original image, aligning it with the painting, and then investigating edge-based differences to understand how artists establish focal areas.
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.