Abstract
We present a new stylization method to generate Random-needle Embroidery stitches which is a graceful Chinese embroidery art formed by intersecting stitches. First, we model the intersecting stitch and initialize stitches positions and directions for regions. The Markov chain model is used to select similar intersecting stitches for filling each region to avoid artifacts in local area. Then a hierarchical iterative stitches generation process is used to keep the characteristic of multi-layering of stitches. Finally, top layer stitches in each iteration of the generation process are slightly moved according to bottom stitches by a Lloyd’s method based approach to make stitches maintain the characteristic of uniform distribution. Experiments show that our result stitches can avoid artifacts in local area and maintain the uniformity and multi-layering at the same time. Comparing with the state-of-the-art methods, our result stitches have a richer visual effect.
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Acknowledgement
This work was supported by National High Technology Re-search and Development Program of China (No. 2007AA01Z334), National Natural Science Foundation of China (Nos. 61321491 and 61272219), Program for New Century Excellent Talents in University of China (NCET-04-04605), the China Postdoctoral Science Foundation (Grant No. 2017M621700) and Innovation Fund of State Key Lab for Novel Software Technology (Nos. ZZKT2013A12, ZZKT2016A11 and ZZKT2018A09).
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Ma, C., Sun, Z., Wu, H., Guo, Y. (2018). Stitches Generation for Random-Needle Embroidery Based on Markov Chain Model. In: Hong, R., Cheng, WH., Yamasaki, T., Wang, M., Ngo, CW. (eds) Advances in Multimedia Information Processing – PCM 2018. PCM 2018. Lecture Notes in Computer Science(), vol 11166. Springer, Cham. https://doi.org/10.1007/978-3-030-00764-5_62
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DOI: https://doi.org/10.1007/978-3-030-00764-5_62
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