A simplified method of detecting structure in Glass patterns
Pattern Recognition Letters
Paint by numbers: abstract image representations
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Edge detection in multispectral images
CVGIP: Graphical Models and Image Processing
Processing images and video for an impressionist effect
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Painterly rendering with curved brush strokes of multiple sizes
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
A neural model of contour integration in the primary visual cortex
Neural Computation
An algorithm for automatic painterly rendering based on local source image approximation
NPAR '00 Proceedings of the 1st international symposium on Non-photorealistic animation and rendering
Abstracted painterly renderings using eye-tracking data
NPAR '02 Proceedings of the 2nd international symposium on Non-photorealistic animation and rendering
Artistic Vision: painterly rendering using computer vision techniques
NPAR '02 Proceedings of the 2nd international symposium on Non-photorealistic animation and rendering
Stylization and abstraction of photographs
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Tutorial: A Survey of Stroke-Based Rendering
IEEE Computer Graphics and Applications
Interactive vector fields for painterly rendering
GI '05 Proceedings of Graphics Interface 2005
Continuous glass patterns for painterly rendering
IEEE Transactions on Image Processing
The Theory of the Moir Phenomenon: Volume I Periodic Layers
The Theory of the Moir Phenomenon: Volume I Periodic Layers
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The theory of Glass patterns naturally combines three essential aspects of painterly artworks: perception, randomness, and geometric structure. Therefore, it seems a suitable framework for the development of mathematical models of the visual properties that distinguish paintings from photographic images. With this contribution, we introduce a simple mathematical operator which transfers the microstructure of a Glass pattern to an input image, and we show that its output is perceptually similar to a painting. An efficient implementation is presented. Unlike most of the existing techniques for unsupervised painterly rendering, the proposed approach does not introduce 'magic numbers' and has a nice and compact mathematical description, which makes it suitable for further theoretical analysis. Experimental results on a broad range of input images validate the effectiveness of the proposed method in terms of lack of undesired artifacts, which are present with other existing methods, and easy interpretability of the input parameters.