TY - GEN
T1 - Glass Patterns and Artistic Imaging
AU - Papari, Giuseppe
AU - Petkov, Nicolai
N1 - Relation: http://www.rug.nl/informatica/organisatie/overorganisatie/iwi
Rights: University of Groningen, Research Institute for Mathematics and Computing Science (IWI)
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
KW - NEURONS
M3 - Conference contribution
SN - 978-3-540-92956-7
T3 - Lecture Notes in Computer Science
SP - 1034
EP - 1045
BT - ADVANCES IN IMAGE AND VIDEO TECHNOLOGY, PROCEEDINGS
A2 - Wada, T
A2 - Huang, F
A2 - Lin, S
PB - Springer
CY - BERLIN
T2 - 3rd Pacific-Rim Symposium on Image and Video Technology (PSIVT 2009)
Y2 - 13 January 2009 through 16 January 2009
ER -