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This paper shows that shape simplification is a tool useful in Non-Photorealistic rendering from photographs, because it permits a level of abstraction otherwise unreachable. A variety of simple shapes (e.g. circles, triangles, squares, superellipses and so on) are optimally fitted to each region within a segmented photograph. The system automatically chooses the shape that best represents the region; the choice is made via a supervised classifier so the 'best shape' depends on the subjectivity of a user. The whole process is fully automatic, aside from the setting of two user variables to control the number of regions in a pair of segmentations - and even these can be left fixed for many images. A gallery of results shows how this work reaches towards the art of later Matisse, of Kandinsky, and other artists who favored shape simplification in their paintings.