A realization method and application of a personal stylized calligraphy dynamic font library
An implementation method and stylized technology, applied in special data processing applications, electrical digital data processing, image data processing and other directions, can solve the problems of lack of handwriting diversity, stereotypes, low efficiency, etc., to improve the interest and level of calligraphy. , the effect of increasing the speed of transmission
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Embodiment 1
[0030] Embodiment 1, a method for realizing a personal stylized calligraphy dynamic font library. The realization method uses statistical machine learning technology to allow the computer to realize the accuracy of the writer through multi-dimensional modeling of the spatial movement trajectory of the writer during the writing process. The purpose of automatic learning of pen movement habits; and then generate a personal stylized calligraphy dynamic font library through virtual reality technology or robot system; the specific steps are as follows:
[0031] 1. Establish a three-dimensional computer model of the brush;
[0032]The brush is composed of a pen holder and a brush; the pen holder is a rigid body, which can be modeled with a cylindrical rod-shaped rigid body; the brush is a soft body, whose root is fixedly connected to the end of the pen holder; the brush is modeled using a spring-mass model, Specifically, the brush skeleton and the layered structure of the brush su...
Embodiment 2
[0108] In Example 2, different writers have basically the same way of holding and wielding the pen, and the differences are often caused by subtle differences in pen-handling habits caused by different aesthetics. Then we can first establish a generalized spatial statistical model of writers' brushwork to reflect the regularity of general writers' brushwork. Then adjust the parameters of the generalized statistical model according to the handwriting of a certain writer, so that it approximates the pen-handling habit of the writer; the spatial statistical models of pen-handling of several writers obtained in step 4 in embodiment 1 can be utilized to generate a A generalized spatial statistical model of the writer's handwriting, which can be used to derive the statistical model of his handwriting from a small number of personal plane handwriting; and then adjust the parameters of the generalized statistical model according to the handwriting of a certain writer to approximate the...
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