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作 者:张攀 周芳利[3] 杨彪 袁丽萍 魏星如 ZHANG Pan;ZHOU Fangli;YANG Biao;YUAN Liping;WEI Xingru(Data Recovery Key Laboratory of Sichuan Province,Neijiang Normal University,Neijiang,Sichuan 641100,China;School of Artificial Intelligence,Neijiang Normal University,Neijiang,Sichuan 641100,China;Sichuan Center for Zhang Daqian Studies,Neijiang Normal University,Neijiang,Sichuan 641100,China)
机构地区:[1]内江师范学院数据恢复四川省重点实验室,四川内江641100 [2]内江师范学院人工智能学院,四川内江641100 [3]内江师范学院四川张大千研究中心,四川内江641100
出 处:《内江师范学院学报》2024年第6期55-59,共5页Journal of Neijiang Normal University
基 金:内江师范学院大学生创新创业训练计划资助项目(X2022038)。
摘 要:针对当前整理张大千书法为字库过程中过度依赖手工标记而采用数字化技术不足的问题,该文提出一种智能化的字库构建方法.该方法首先利用具备多尺度特征提取能力的深度学习目标检测算法YOLOv3,实现对相关书法作品中多种尺寸文字图像的自动检测、定位与采集.其次,利用具有U型结构编解码器的深度学习图像分割算法U-Net,实现对背景纹理自相似文字图像中笔画前景细节的有效分离.随后,利用图像矢量化技术实现文字图像的数字化转换.最终结合字体编辑软件FontForge实现包含1893个文字的大千字库的构建,为张大千书法研究提供进一步的数字化支撑.An intelligent method for constructing a font library is proposed in this article to address the issue of excessive reliance on manual marking and insufficient use of digital technology in the current process of feeding Zhang Daqian’s calligraphy into a font library.With such a method,the deep learning object detection algorithm YOLOv3,known for its ability to extract multi-scale features,is employed for the operation of the automatic detection,positioning,and collection of text images of various sizes from relevant calligraphy works.Furthermore,the deep learning image segmentation algorithm U-Net,featuring a U-shaped structure codec,is utilized to achieve effective separation of foreground details of text strokes from the self-similar background textures in collected images.Subsequently,image vectorization technology is used to achieve the digital conversion of text images.Finally,FontForge,a font editing software,is combined with the aforementioned processes to construct a comprehensive font library comprising 1893 characters.This library provides further digital support for research into Zhang Daqian’s calligraphy.
关 键 词:大千字库 智能化构建 目标检测 图像分割 图像矢量化
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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