Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76117
Title: ASCII art synthesis from natural photographs
Authors: Xu, XM
Zhong, LY
Xie, MS
Liu, XT
Qin, J 
Wong, TT
Keywords: ASCII art synthesis
Non-classical receptive field modulation
Texture suppression
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on visualization and computer graphics, 2017, v. 23, no. 8, p. 1910-1923 How to cite?
Journal: IEEE transactions on visualization and computer graphics 
Abstract: 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.
URI: http://hdl.handle.net/10397/76117
ISSN: 1077-2626
EISSN: 1941-0506
DOI: 10.1109/TVCG.2016.2569084
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