Currently,the intelligent character creation technology based on style learning generates fonts with low similarity to the user's handwritten style,and the method based on Graphics Processing Unit(GPU)style transfer is expensive.To solve the problems above,a new intelligent character creation method is proposed using deep learning and image segmentation technology,which can maintain a highly similar style while meeting the personalized needs and reducing the generation cost.Using DeepLab v3+technology,775 font images input by users are filtered by a data quality evaluation model and are split to components by image segmentation models.Then,components are finely adjusted and noise is removed,and finally TrueType fonts are generated after vectorization.Compared with existing technologies,this method significantly improves the similarity and reduces the cost,and can effectively meet the personalized customization needs of users.
关键词
智能造字/DeepLab/v3+/数据质量评估模型/图像分割模型/TrueType
Key words
intelligent character creation/DeepLab v3+/data quality evaluation model/image segmentation model/Truetype
维普
万方数据