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Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2021,5,31]]},"abstract":"<jats:p>Brushstrokes are viewed as the artist\u2019s \u201chandwriting\u201d in a painting. In many applications such as style learning and transfer, mimicking painting, and painting authentication, it is highly desired to quantitatively and accurately identify brushstroke characteristics from old masters\u2019 pieces using computer programs. However, due to the nature of hundreds or thousands of intermingling brushstrokes in the painting, it still remains challenging. This article proposes an efficient algorithm for brush Stroke extraction based on a Deep neural network, i.e., DStroke. Compared to the state-of-the-art research, the main merit of the proposed DStroke is to automatically and rapidly extract brushstrokes from a painting without manual annotation, while accurately approximating the real brushstrokes with high reliability. Herein, recovering the faithful soft transitions between brushstrokes is often ignored by the other methods. In fact, the details of brushstrokes in a master piece of painting (e.g., shapes, colors, texture, overlaps) are highly desired by artists since they hold promise to enhance and extend the artists\u2019 powers, just like microscopes extend biologists\u2019 powers. To demonstrate the high efficiency of the proposed DStroke, we perform it on a set of real scans of paintings and a set of synthetic paintings, respectively. Experiments show that the proposed DStroke is noticeably faster and more accurate at identifying and extracting brushstrokes, outperforming the other methods.<\/jats:p>","DOI":"10.1145\/3429742","type":"journal-article","created":{"date-parts":[[2021,5,12]],"date-time":"2021-05-12T00:56:03Z","timestamp":1620780963000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Fast Accurate and Automatic Brushstroke Extraction"],"prefix":"10.1145","volume":"17","author":[{"given":"Yunfei","family":"Fu","sequence":"first","affiliation":[{"name":"iArt.ai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongchuan","family":"Yu","sequence":"additional","affiliation":[{"name":"National Centre for Computer Animation, Bournemouth University, Fern Barrow, Poole, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chih-Kuo","family":"Yeh","sequence":"additional","affiliation":[{"name":"School of Computer Science and Software, Zhaoqing University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tong-Yee","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Cheng-Kung University, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian J.","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Centre for Computer Animation, Bournemouth University, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,5,11]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.32"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3197517.3201275"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3092919.3092926"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/2489244.2501802"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.18"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"e_1_2_1_7_1","article-title":"High relief from brush painting","volume":"10","author":"Fu Y.","year":"2018","unstructured":"Y. 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