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The method of combining end-to-end techniques and physical models requires further study, however, it is difficult to obtain large amounts of brush strokes for deep learning and training. To overcome this, we propose using a simulated brush model to train a generator based on the B\u00e9zier brush stroke model generator (B-BSMG), which was formed by two symmetric cubic B\u00e9zier curves according to the physical characteristics and writing posture of the brush. The B-BSMG can generate images for deep learning and training using a dataset simulated by the B\u00e9zier brush stroke model. Our renderer is based on parameterized brush strokes, providing a better foundation for deep learning or robotic writing. The results of several experiments prove that the proposed B-BSMG can generate stroke graphics well and outperforms other advanced stroke models.<\/jats:p>","DOI":"10.1007\/s44196-024-00499-4","type":"journal-article","created":{"date-parts":[[2024,4,25]],"date-time":"2024-04-25T08:02:09Z","timestamp":1714032129000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["B-BSMG: B\u00e9zier Brush Stroke Model-Based Generator for Robotic Chinese Calligraphy"],"prefix":"10.1007","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6100-4273","authenticated-orcid":false,"given":"Dongmei","family":"Guo","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5439-1989","authenticated-orcid":false,"given":"Guang","family":"Yan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,4,25]]},"reference":[{"issue":"7","key":"499_CR1","doi-asserted-by":"publisher","first-page":"1665","DOI":"10.13195\/j.kzyjc.2021.0132","volume":"37","author":"DM Guo","year":"2022","unstructured":"Guo, D.M., Min, H.S.: Survey of calligraphy robot. 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