Method of generating font database, and method of training neural network model
AssigneeBeijing Baidu Netcom Science Technology Co., Ltd.
InventorsLicheng Tang, Jiaming Liu
Life of this patent
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Abstract
A method of generating a font database, and a method of training a neural network model are provided, which relate to a field of artificial intelligence, in particular to a computer vision and deep learning technology. The method of generating the font database includes: determining, by using a trained similarity comparison model, a basic font database most similar to handwriting font data of a target user in a plurality of basic font databases as a candidate font database; and adjusting, by using a trained basic font database model for generating the candidate font database, the handwriting font data of the target user, so as to obtain a target font database for the target user.
Claims16
A method of generating a font database, comprising:
- determining, by using a trained similarity comparison model, a basic font database most similar to handwriting font data of a target user in a plurality of basic font databases as a candidate font database;
- and
- adjusting, by using a trained basic font database model for generating the candidate font database, the handwriting font data of the target user, so as to obtain a target font database for the target user, wherein
- the adjusting, by using the trained basic font database model for generating the candidate font database, the handwriting font data of the target user includes:
- using a basic stroke of a standard font as an input of the trained basic font database model for generating the candidate font database;
- and
- using a basic stroke of the handwriting font of the target user as an output of the trained basic font database model for generating the candidate font database;
- and
- the basic stroke of the handwriting font of the target user is obtained by segmenting a handwritten word of the target user using a coherent point drift (CPD) matching algorithm.
A method of training a neural network model comprising a basic font database model and a similarity comparison model, comprising:
- training the basic font database model using handwriting font data of a plurality of users, so that each user of the plurality of users has a corresponding basic font database model and a corresponding basic font database;
- and
- training the similarity comparison model using a plurality of basic font databases of the plurality of users, wherein
- the training the basic font database model using handwriting font data of a plurality of users includes:
- using a basic stroke of a standard font as an input;
- and
- using a basic stroke of a handwriting font of each user of the plurality of users as an output;
- and
- the basic stroke of the handwriting font of each user of the plurality of users is obtained by segmenting a handwritten word of the user using a coherent point drift (CPD) matching algorithm.
Dependencies are inferred from the claim text.