Texture-Aware ASCII Art Synthesis with Proportional Fonts: Unterschied zwischen den Versionen

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  pages = {183--193},
 
  pages = {183--193},
 
  numpages = {11},
 
  numpages = {11},
  url = {http://dl.acm.org/citation.cfm?id=2810002.2810009 },
+
  url = {http://dl.acm.org/citation.cfm?id=2810002.2810009 http://de.evo-art.org/index.php?title=Texture-Aware_ASCII_Art_Synthesis_with_Proportional_Fonts },
url = {http://de.evo-art.org/index.php?title=Texture-Aware_ASCII_Art_Synthesis_with_Proportional_Fonts },
 
 
  acmid = {2810009},
 
  acmid = {2810009},
 
  publisher = {Eurographics Association},
 
  publisher = {Eurographics Association},

Aktuelle Version vom 2. November 2015, 21:45 Uhr

Reference

Xuemiao Xu, Linyuan Zhong, Minshan Xie, Jing Qin, Yilan Chen, Qiang Jin, Tien-Tsin Wong, and Guoqiang Han: Texture-Aware ASCII Art Synthesis with Proportional Fonts. In: Computational Aesthetics 2015 NPAR'15, 183-193.

DOI

http://dx.doi.org/10.2312/exp.20151191

Abstract

We present a fast structure-based ASCII art generation method that accepts arbitrary images (real photograph or hand-drawing) as input. Our method supports not only fixed width fonts, but also the visually more pleasant and computationally more challenging proportional fonts, which allows us to represent challenging images with a variety of structures by characters. We take human perception into account and develop a novel feature extraction scheme based on a multi-orientation phase congruency model. Different from most existing contour detection methods, our scheme does not attempt to remove textures as much as possible. Instead, it aims at faithfully capturing visually sensitive features, including both main contours and textural structures, while suppressing visually insensitive features, such as minor texture elements and noise. Together with a deformation-tolerant image similarity metric, we can generate lively and meaningful ASCII art, even when the choices of character shapes and placement are very limited. A dynamic programming based optimization is proposed to simultaneously determine the optimal proportional-font characters for matching and their optimal placement. Experimental results show that our results outperform state-of-the-art methods in term of visual quality.

Extended Abstract

Bibtex

@inproceedings{Xu:2015:TAA:2810002.2810009,
author = {Xu, Xuemiao and Zhong, Linyuan and Xie, Minshan and Qin, Jing and Chen, Yilan and Jin, Qiang and Wong, Tien-Tsin and Han, Guoqiang},
title = {Texture-aware ASCII Art Synthesis with Proportional Fonts},
booktitle = {Proceedings of the Workshop on Non-Photorealistic Animation and Rendering},
series = {NPAR '15},
year = {2015},
location = {Istanbul, Turkey},
pages = {183--193},
numpages = {11},
url = {http://dl.acm.org/citation.cfm?id=2810002.2810009 http://de.evo-art.org/index.php?title=Texture-Aware_ASCII_Art_Synthesis_with_Proportional_Fonts },
acmid = {2810009},
publisher = {Eurographics Association},
address = {Aire-la-Ville, Switzerland, Switzerland},
}

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