Deep stacking network-based structure information guided Chinese character library generation method

Abstract

The invention discloses an automatic generation method of a handwritten Chinese character library, which comprises the following steps of: predicting a Chinese character skeleton flow field by adopting a two-stage convolutional neural network G through a writing track synthesis stage and a font style rendering stage on the basis of a deep stacking network and structure information guidance; firstly, the writing style is learned from a small amount of handwritten Chinese characters written by a user, so that the writing track of unwritten Chinese characters is synthesized; The handwriting styleof the target is rendered; and generating a complete GB2312 Chinese handwriting word stock file with the writing style of the user. The method can ensure the structural accuracy and style consistencyof the generated fonts at the same time, is simple, efficient, low in cost and high in quality, and can meet the actual application requirements of ordinary people for quickly making personalized handwriting fonts.

Description

technical field [0001] The invention belongs to the technical fields of computer graphics and image processing, artificial intelligence and deep learning, and relates to Chinese word processing technology, in particular to a method for automatically generating a handwritten Chinese character library guided by structural information based on a deep stacking network. Based on empirical knowledge and deep neural network, it learns writing style and generates a complete Chinese character library. Background technique [0002] Personalized fonts make information dissemination more vivid and intuitive. Compared with standardized printing fonts, more and more people hope to use personalized fonts, especially handwriting fonts, in electronic mobile devices to communicate and communicate. On the one hand, personalized fonts can render text into a unique writing style, expressing the writer's style and feelings more flexibly; on the other hand, the visual effects of personalized font...

AI Technical Summary

Problems solved by technology

However, the entire generation process is uncontrollable and unpredictable, and blurring and false edges are unavoidable in the generated Chinese character images

In addition, for Chinese characters with complex structures or sloppy writing styles, end-to-end methods often get unreasonable strokes or even wrong Chinese character structures

Images