Hidden curve removal for free form surfaces
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Rendering parametric surfaces in pen and ink
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Texture mapping for cel animation
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Interactive technical illustration
I3D '99 Proceedings of the 1999 symposium on Interactive 3D graphics
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Image quilting for texture synthesis and transfer
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Non-Photorealistic Rendering
Digital Image Processing
Transferring color to greyscale images
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Output Sensitive Extraction of Silhouettes from Polygonal Geometry
PG '99 Proceedings of the 7th Pacific Conference on Computer Graphics and Applications
IEEE Computer Graphics and Applications
Multiparent recombination in evolutionary computing
Advances in evolutionary computing
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Bio-inspired computing: constituents and challenges
International Journal of Bio-Inspired Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Modified Adaptive Cuckoo Search (MACS) algorithm and formal description for global optimisation
International Journal of Computer Applications in Technology
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NPR may be seen as any attempt to create images to convey a scene without directly rendering a physical simulation. This paper describes an evolutionary algorithm (EA) for learning painting styles from example images. The evolutionary algorithm has two main stages: learning and painting. By learning the painting style from a source pair of training images (a source photograph and its artistic style), a style approximation can then be accomplished to another target image. The mechanism of evolutionary algorithms is used here to learn or capture different characters used to depict different regions of the source painting and use them to convert similar regions with similar texture statistics of the target image into artistic rendering. Two main perturbation operators are used in the proposed EA: a multi-sexual recombination and mutation operators. On overall, the algorithm, with its implementation simplicity and computation efficiency, can provide acceptable results with perceived artistic rendering.