TY - CPAPER
KW - Textile printing
KW - Image segmentation
KW - Color
KW - Rendering (computer graphics)
KW - Image-based
KW - Image-based artistic rendering
KW - Needles
KW - Random-needle embroidery
KW - Stitch selection
KW - Color quantization
KW - Image compression
KW - Sparse modeling
AU - Kewei Yang
AU - Zhengxing Sun
AU - Shuang Wang
AU - Hui-Hsia Chen
AB - We present an image stylization method to simulate a graceful Chinese art—Random-needle Embroidery designated as Intangible Cultural Heritage. We first develop an effective way to simulate a single thread, and define rendering primitive called stitch which is a collection of threads arranged in a certain pattern. Then, we segment the input image and partition each region into non-uniform sub-regions, from which a color quantization method is proposed to select colors used in the rendering process for each sub-region from a specific color library. During runtime, new stitches can be synthesized for each sub-region via sparse modeling based on the pre-defined stitches. Smoothness constraints are added to this process to avoid local distortions. Finally, rendering image is generated by placing stitches with different attributes on the canvas. Experiments show that our method can perform fine images with the style of random-needle.
DO - 10.1007/978-3-319-77380-3_49
LA - English
N1 - Journal Abbreviation: Lect. Notes Comput. Sci. Pages: 525 Publication Title: Lect. Notes Comput. Sci.
N2 - We present an image stylization method to simulate a graceful Chinese art—Random-needle Embroidery designated as Intangible Cultural Heritage. We first develop an effective way to simulate a single thread, and define rendering primitive called stitch which is a collection of threads arranged in a certain pattern. Then, we segment the input image and partition each region into non-uniform sub-regions, from which a color quantization method is proposed to select colors used in the rendering process for each sub-region from a specific color library. During runtime, new stitches can be synthesized for each sub-region via sparse modeling based on the pre-defined stitches. Smoothness constraints are added to this process to avoid local distortions. Finally, rendering image is generated by placing stitches with different attributes on the canvas. Experiments show that our method can perform fine images with the style of random-needle.
PB - Springer Verlag
PY - 2018
SN - 03029743 (ISSN); 9783319773797 (ISBN)
SP - 515
EP - 525
TI - Image Stylization for Thread Art via Color Quantization and Sparse Modeling
UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047467133&doi=10.1007%2f978-3-319-77380-3_49&partnerID=40&md5=26b34b6dcd3922d8aea22a91ced54a6e
VL - 10735 LNCS
ER -