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Title: Exploring the space of abstract textures by principles and random sampling
Authors: Alvarez, Luis 
Gousseau, Yann
Morel, Jean Michel
Salgado, Agustín
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
120326 Simulación
Keywords: Abstract painting
Dead leaves model
Gestalt theory
Graphic design
Texture synthesis
Issue Date: 2015
Journal: Journal of Mathematical Imaging and Vision 
Abstract: Exemplar-based texture synthesis methods try to emulate textures observed in our visual world. Yet the field of all possible textures (natural or not) has been little explored. Indeed, existing abstract synthesis methods focus on a single generation rule and generate a rather limited set of textures. This limitation can be overcome by combining randomly various generation principles and rule parameters. Doing so gives access to a vast and still unexplored set of possible images. In this paper, we introduce an image sampling method combining the main painting techniques of abstract art. This sampler synthesizes what we call multi-layered textures. The underlying image model extends three abstract image synthesis models: the dead leaves model, the spot noise, and fractal generators. By respecting minimal self-similarity rules keeping Gestalt theory grouping principles at each texture layer, the abstract textures remain understandable to human perception. The complexity of the generated textures derives from the systematic and randomized use of shape interaction principles taken from abstract art such as occlusion, transparency, exclusion, inclusion, and tessellation.
ISSN: 0924-9907
DOI: 10.1007/s10851-015-0582-z
Source: Journal of Mathematical Imaging and Vision [ISSN 0924-9907], v. 53 (3), p. 332-345
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