Abstract
Chinese calligraphy is the artistic expression of character writing and is highly valued in East Asia. However, it is a challenge for non-expert users to write visually pleasing calligraphy with his or her own unique style. In this paper, we develop an intelligent system that beautifies Chinese handwriting characters and physically writes them in a certain calligraphy style using a robotic arm. First, we sketch the handwriting characters using a mouse or a touch pad. Then, we employ a convolutional neural network to identify each stroke from the skeletons, and the corresponding standard stroke is retrieved from a pre-built calligraphy stroke library for robotic arm writing. To output aesthetically beautiful calligraphy with the user’s style, we propose a global optimization approach to solve the minimization problem between the handwritten strokes and standard calligraphy strokes, in which a shape character vector is presented to describe the shape of standard strokes. Unlike existing systems that focus on the generation of digital calligraphy from handwritten characters, our system has the advantage of converting the user-input handwriting into physical calligraphy written by a robotic arm. We take the regular script (Kai) style as an example and perform a user study to evaluate the effectiveness of the system. The writing results show that our system can achieve visually pleasing calligraphy from various input handwriting while retaining the user’s style.
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Chao, F., Lv, J., Zhou, D., Yang, L., Lin, C., Shang, C., Zhou, C.: Generative adversarial nets in robotic Chinese calligraphy. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 1104–1110 (2018)
Chen, X., Lian, Z., Tang, Y., Xiao, J.: A benchmark for stroke extraction of Chinese character. Acta Sci. Nat. Univ. Pekin. 52(1), 49–57 (2016)
Dobot Robotic Arms: https://www.dobot.cc/. Accessed on Feb 10, 2019
Furrer, F., Wermelinger, M., Yoshida, H., Gramazio, F., Kohler, M., Siegwart, R., Hutter, M.: Autonomous robotic stone stacking with online next best object target pose planning. In: 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 2350–2356 (2017)
Gupta, A., Srivastava, M., Mahanta, C.: Offline handwritten character recognition using neural network. In: 2011 IEEE International Conference on Computer Applications and Industrial Electronics (ICCAIE), pp. 102–107 (2011)
Hashiguchi, H., Arimoto, S., Ozawa, R.: Control of a handwriting robot with DOF-redundancy based on feedback in task-coordinates. J. Robot. Mechatron. 16, 381–387 (2004)
Igarashi, T., Inami, M.: Exploration of alternative interaction techniques for robotic systems. IEEE Comput. Graph. Appl. 35(3), 33–41 (2015)
Igarashi, T., Matsuoka, S., Tanaka, H.: Teddy: A sketching interface for 3D freeform design. In: SIGGRAPH’99, pp. 409–416, New York (1999)
Kim, B., Wang, O., Öztireli, A.C., Gross, M.: Semantic segmentation for line drawing vectorization using neural networks. Comput. Graph. Forum 37(2), 329–338 (2018)
Kim, S., Jo, J., Oh, Y., Oh, S., Srinivasa, S., Likhachev, M.: Robotic handwriting: multi-contact manipulation based on reactional internal contact hypothesis. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 877–884 (2014)
Krizek, M., Neittaanmki, P., Glowinski, R., Korotov, S.: Conjugate Gradient Algorithms and Finite Element Methods. Springer, Berlin (2004)
Li, H., Liu, P., Xu, S., Lin, S.: Calligraphy beautification method for Chinese handwritings. In: 2012 4th International Conference on Digital Home, pp. 122–127 (2012)
Liu, L., Xia, W., Jin, L., Mao, H., Tian, F.: A Kai style contour beautification method for Chinese handwriting characters. In: 2010 IEEE International Conference on Systems, Man and Cybernetics, pp. 3644–3649 (2010)
Lo, K.W., Kwok, K.W., Wong, S.M., Yam, Y.: Brush footprint acquisition and preliminary analysis for Chinese calligraphy using a robot drawing platform. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5183–5188 (2006)
Ma, Z., Su, J.: Aesthetics evaluation for robotic Chinese calligraphy. IEEE Trans. Cogn. Dev. Syst. 9(1), 80–90 (2017)
Mueller, S., Huebel, N., Waibel, M., D’Andrea, R.: Robotic calligraphy-learning how to write single strokes of Chinese and Japanese characters. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1734–1739 (2013)
Okutomi, M.: Digital Image Processing. The Computer Graphic Arts Society (CG-ARTS), Tokyo (2015)
Online Chinese Calligraphy Generator: https://www.zhenhaotv.com/. Accessed on Dec. 4, 2018
Sun, Y., Ding, N., Qian, H., Xu, Y.: A robot for classifying Chinese calligraphic types and styles. In: 2013 IEEE International Conference on Robotics and Automation, pp. 4279–4284 (2013)
Sun, Y., Qian, H., Xu, Y.: A geometric approach to stroke extraction for the Chinese calligraphy robot. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 3207–3212 (2014)
Sun, Y., Qian, H., Xu, Y.: Robot learns Chinese calligraphy from demonstrations. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4408–4413. IEEE, New York (2014)
Syamlan, A.T., Nurhadi, H., Pramujati, B.: Character recognition for writing robot control using ANFIS. In: 2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA), pp. 46–48 (2015)
Tian, X., Tian, Y.: The Elaboration of Ancient and Modern Famous Kai Calligraphy. Jiangxi Fine Arts Press, Jiangxi (2007)
Xiao, X., Jin, L., Yang, Y., Yang, W., Sun, J., Chang, T.: Building fast and compact convolutional neural networks for offline handwritten Chinese character recognition. Pattern Recognit. 72, 72–81 (2017)
Yao, F., Shao, G., Yi, J.: Trajectory generation of the writing-brush for a robot arm to inherit block-style Chinese character calligraphy techniques. Adv. Robot. 18(3), 331–356 (2004)
Yi, T., Lian, Z., Tang, Y., Xiao, J.: A data-driven personalized digital ink for Chinese characters. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds.) MultiMedia Modeling, pp. 254–265. Springer, New York (2014). https://doi.org/10.1007/978-3-319-04114-8
Zeng, H., Huang, Y., Chao, F., Zhou, C.: Survey of robotic calligraphy research. CAAI Trans. Intell. Syst. 11(1), 15–26 (2016)
Zhang, Z., Wu, J., Yu, K.: Chinese calligraphy specific style rendering system. In: Proceedings of the ACM International Conference on Digital Libraries, pp. 99–108 (2010)
Acknowledgements
We thank the CGI2019 reviewers for their thoughtful comments. The work is supported by the NSFC (61303124), NSBR Plan of Shaanxi (2019JM370) and the Fundamental Research Funds for the Central Universities (2452017343).
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Zhang, X., Li, Y., Zhang, Z. et al. Intelligent Chinese calligraphy beautification from handwritten characters for robotic writing. Vis Comput 35, 1193–1205 (2019). https://doi.org/10.1007/s00371-019-01675-w
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DOI: https://doi.org/10.1007/s00371-019-01675-w