ASCII Art Synthesis from Natural Photographs

While ASCII art is a worldwide popular art form, automatic generating structure-based ASCII art from natural photographs remains challenging. The major challenge lies on extracting the perception-sensitive structure from the natural photographs so that a more concise ASCII art reproduction can be pr...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 23(2017), 8 vom: 01. Aug., Seite 1910-1923
1. Verfasser: Xu, Xuemiao (VerfasserIn)
Weitere Verfasser: Zhong, Linyuan, Xie, Minshan, Liu, Xueting, Qin, Jing, Wong, Tien-Tsin
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2017
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
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520 |a While ASCII art is a worldwide popular art form, automatic generating structure-based ASCII art from natural photographs remains challenging. The major challenge lies on extracting the perception-sensitive structure from the natural photographs so that a more concise ASCII art reproduction can be produced based on the structure. However, due to excessive amount of texture in natural photos, extracting perception-sensitive structure is not easy, especially when the structure may be weak and within the texture region. Besides, to fit different target text resolutions, the amount of the extracted structure should also be controllable. To tackle these challenges, we introduce a visual perception mechanism of non-classical receptive field modulation (non-CRF modulation) from physiological findings to this ASCII art application, and propose a new model of non-CRF modulation which can better separate the weak structure from the crowded texture, and also better control the scale of texture suppression. Thanks to our non-CRF model, more sensible ASCII art reproduction can be obtained. In addition, to produce more visually appealing ASCII arts, we propose a novel optimization scheme to obtain the optimal placement of proportional-font characters. We apply our method on a rich variety of images, and visually appealing ASCII art can be obtained in all cases 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
700 1 |a Zhong, Linyuan  |e verfasserin  |4 aut 
700 1 |a Xie, Minshan  |e verfasserin  |4 aut 
700 1 |a Liu, Xueting  |e verfasserin  |4 aut 
700 1 |a Qin, Jing  |e verfasserin  |4 aut 
700 1 |a Wong, Tien-Tsin  |e verfasserin  |4 aut 
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