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Extracting the trajectory of writing brush in Chinese character calligraphy

机译:提取汉字书法笔迹的轨迹

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This paper describes the extraction of the trajectory of the writing brush in Chinese character calligraphy (CCC), based on image and curve processing techniques and the calligraphy knowledge. This trajectory is used in a CCC robot which is developed to inherit CCC techniques. In CCC, the writing styles can be roughly classified into five different styles-ancient, angular, block, semi-cursive, and cursive style. This paper is limited to discuss the trajectory extraction from the character image written in block style. Firstly, for a given Chinese character, its image patterns in block style are retrieved from CCC database which contains 29.456 characters written by different famous calligraphers in Chinese history. Then the image of the designated writing is thinned. The coordinates of the line passing the centers of each stroke are detected from the thinned image with aid of writing order information. These coordinates represent the thinned-center-line of the stroke (TCLS, for short). And then, TCLS is separated into several curve segments according the calligraphy knowledge. The trajectory of the writing brush is considered as B-spline curves determined by the points on curve segments. The trajectory and the pressure control information are sent to the CCC robot to imitate calligrapher's behavior. The experiment results show that the proposed method obtains very good trajectories of the writing brush for CCC robot.
机译:本文基于图像和曲线处理技术以及书法知识,描述了汉字书法(CCC)毛笔轨迹的提取。该轨迹用于CCC机器人中,该机器人被开发来继承CCC技术。在CCC中,写作风格可以粗略地分为五种风格:古代,棱角,方块,半草书和草书风格。本文仅限于讨论以块样式书写的字符图像的轨迹提取。首先,对于给定的汉字,从CCC数据库中检索其块样式的图像模式,该数据库包含29.456个由中国历史上著名书法家书写的字符。然后,指定文字的图像被细化。借助于书写顺序信息,从细化图像中检测出通过每个笔画的中心的线的坐标。这些坐标代表笔划的细线(TCLS,简称)。然后,根据书法知识将TCLS分为几个曲线段。笔刷的轨迹被视为由曲线段上的点确定的B样条曲线。轨迹和压力控制信息被发送到CCC机器人,以模仿书法家的行为。实验结果表明,该方法获得了CCC机器人笔刷的良好轨迹。

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