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Image Stylization for Thread Art via Color Quantization and Sparse Modeling

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10735))

Abstract

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.

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Acknowledgement

This work was supported by National High Technology Research and Development Program of China (No. 2007AA01Z334), National Natural Science Foundation of China (Nos. 61321491 and 61272219), Innovation Fund of State Key Laboratory for Novel Software Technology (Nos. ZZKT2013A12 and ZZKT2016A11), and Program for New Century Excellent Talents in University of China (NCET-04-04605).

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Correspondence to Zhengxing Sun .

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Yang, K., Sun, Z., Wang, S., Chen, HH. (2018). Image Stylization for Thread Art via Color Quantization and Sparse Modeling. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10735. Springer, Cham. https://doi.org/10.1007/978-3-319-77380-3_49

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  • DOI: https://doi.org/10.1007/978-3-319-77380-3_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77379-7

  • Online ISBN: 978-3-319-77380-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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