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Copybook generation system based on deep neural network

A deep neural network and generation system technology, applied in the field of copybook generation, can solve the problems of incomplete font library, no font library, no way to generate, etc.

Pending Publication Date: 2021-07-06
无锡乐骐科技股份有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, one is that the font library of existing fonts is not comprehensive, including the fonts of some big calligraphers, and there is no complete font library. Some systems also have no way to generate corresponding full-text fonts for each user's partial fonts

Method used

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  • Copybook generation system based on deep neural network
  • Copybook generation system based on deep neural network

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Embodiment Construction

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0024] A copybook generation system based on a deep neural network, including a font preparation system, a stroke extraction system, a generation system, and a model building evaluation system;

[0025] The font preparation system transfers handwritten fonts to the system in the form of photos for users;

[0026] The stroke extraction system extracts individual strokes or continuous strokes of fonts in photos;

[0027] The generation system is to learn according t...

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Abstract

The invention provides a copybook generation system based on a deep neural network, and the system comprises a font preparation system, a stroke extraction system, a generation system, and a construction model evaluation system. The font preparation system transmits handwritten fonts to the system in the form of photos for a user. The stroke extraction system is used for respectively extracting single strokes or connected strokes of fonts in a picture, the generation system is used for learning according to the association of the single strokes and the connected strokes to form a font model, and the model evaluation system is constructed for evaluating the quality of the font model so as to form a closest font library. So the method has the advantage that corresponding full-text font library fonts can be formed according to different fonts of each person in a short time.

Description

technical field [0001] The invention belongs to the technical field of copybook generation, in particular to a copybook generation system based on a deep neural network. Background technique [0002] At present, it is well known that there are more than 7,000 Chinese characters and 3,755 commonly used Chinese characters. To design a font, the designer needs to design every Chinese character under the font, and to design a calligrapher font also requires the calligrapher to write almost all the commonly used Chinese characters, which usually takes 2-3 years. [0003] However, one is that the font library of existing fonts is not comprehensive, including the fonts of some big calligraphers, and there is no complete font library. Some systems also have no way to generate corresponding full-text fonts for each user's partial fonts. Contents of the invention [0004] The present invention proposes a copybook generation system based on a deep neural network, which can form fon...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/32G06K9/34G06N3/04G06N3/08
CPCG06N3/08G06V30/347G06V10/243G06V30/153G06N3/045
Inventor 袁存鼎
Owner 无锡乐骐科技股份有限公司
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