Volume 44 (2025)

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Browsing Volume 44 (2025) by Subject "Applied computing → Fine arts"

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    Continuous-Line Image Stylization Based on Hilbert Curve
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Tong, Zhifang; Zuo, Bolei; Yang, Xiaoxia; Liu, Shengjun; Liu, Xinru; Wang, Beibei; Wilkie, Alexander
    Horizontal and vertical lines hold significant aesthetic and psychological importance, providing a sense of order, stability, and security. This paper presents an image stylization method that quickly generates non-self-intersecting and regular continuous lines based on the Hilbert curve, a well-known space-filling curve consisting of only horizontal and vertical segments. We first calculate the grayscale threshold based on gray quantization for the original image and recursively subdivide the cells according to the density in each cell. To avoid generating new feature curves due to limited gray quantization, a recursive subdivision with probability is designed to smooth the density. Then, we utilize the rule of Hilbert curve to generate continuous lines connecting all the cells. Between different degrees of Hilbert curves, bridge curves composed of horizontal and vertical lines are constructed, which are also intersection-free, instead of a straight line linking them directly. There are two parameters provided for feasibly adjusting variate effects. The image stylization framework could be generalized to other space-filling curves like the Peano curve. Compared to existing methods, our approach can generate pleasing results quickly and is fully automated. Many results show our method is robust and effective.
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    Screentone-Preserved Manga Retargeting
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Xie, Minshan; Xia, Menghan; Li, Chengze; Liu, Xueting; Wong, Tien-Tsin; Bousseau, Adrien; Day, Angela
    As a popular comic style, manga offers a unique impression by utilizing a rich set of bitonal patterns, or screentones, for illustration. However, screentones can easily be degraded when manga is resized in terms of aspect ratio and resolution for manga re-layout and e-manga migration applications. To tackle this problem, we propose the first automatic manga retargeting method that synthesizes a retargeted manga image while preserving the prominent structure and fine screentone intended by the manga artist. While modern natural photo retargeting methods can achieve prominent structure preservation, preserving screentones within arbitrarily shaped regions is very challenging due to two properties of manga: (i) pattern constancy under translation, and (ii) non-compatibility with interpolation. To circumvent this barrier, we propose learning a quantized representation of screentones that is translation-invariant and pointwisely representable through a tailored manga reconstruction network with a screentone-anchored codebook. Thanks to these merits, we can perform the re-synthesis operation using existing photo retargeting methods and achieve the desired manga retargeting results.We conducted extensive qualitative and quantitative experiments to validate the effectiveness of our method, and we achieved notably compelling results compared to alternative methods.