Enhancing pencil drawing patterns via using semantic information

Li, Teng; Xie, Jianyu; Niu, Hongliang; Hao, Shijie

doi:10.1007/s11042-021-11028-2

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Cited by 4 publications

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Feature-preserving color pencil drawings from photographs

Wang

Gao

et al. 2023

Comp. Visual Media

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Color pencil drawing is well-loved due to its rich expressiveness. This paper proposes an approach for generating feature-preserving color pencil drawings from photographs. To mimic the tonal style of color pencil drawings, which are much lighter and have relatively lower saturation than photographs, we devise a lightness enhancement mapping and a saturation reduction mapping. The lightness mapping is a monotonically decreasing derivative function, which not only increases lightness but also preserves input photograph features. Color saturation is usually related to lightness, so we suppress the saturation dependent on lightness to yield a harmonious tone. Finally, two extremum operators are provided to generate a foreground-aware outline map in which the colors of the generated contours and the foreground object are consistent. Comprehensive experiments show that color pencil drawings generated by our method surpass existing methods in tone capture and feature preservation.

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