Faraj, NouraXia, Gui-SongDelon, JulieGousseau, YannHolger Winnemoeller and Lyn Bartram2017-10-182017-10-182017978-1-4503-5081-5-https://doi.org/10.1145/3092919.3092930https://diglib.eg.org:443/handle/10.2312/npar2017a09Structural properties are important clues for non-photorealistic representations of digital images. erefore, image analysis tools have been intensively used either to produce stroke-based render- ings or to yield abstractions of images. In this work, we propose to use a hierarchical and geometrical image representation, called a topographic map, made of shapes organized in a tree structure. ere are two main advantages of this analysis tool. Firstly, it is able to deal with all scales, so that every shape of the input image is represented. Secondly, it accounts for the inclusion properties within the image. By iteratively performing simple local operations on the shapes (removal, rotation, scaling, replacement. . . ), we are able to generate abstract renderings of digital photographs ranging from geometrical abstraction and painting-like e ects to style trans- fer, using the same framework. In particular, results show that it is possible to create abstract images evoking Malevitch's Suprematist school, while remaining grounded in the structure of digital images, by replacing all the shapes in the tree by simple geometric shapes.Computing methodologiesNon photorealistic renderingImage processingImage ProcessingImage RepresentationHierarchicalMorphologicalImage abstractionPicture/Image Generation.10.1145/3092919.3092930