Handwritten Calligraphy Font Recognition Algorithm Based on Deep Learning
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    In order to solve the problem of difficult recognition due to the large variety of handwritten calligraphy fonts and reduce the threshold for people to appreciate calligraphy, we propose a handwritten calligraphy font recognition algorithm based on deep learning. In the process of recognition, image processing methods, such as projection method, are first used to locate and segment the Chinese characters in the calligraphy works. Then, the GoogLeNet Inception-v3 model and ResNet-50 residual network are used to recognize the styles and shapes of Chinese characters. Consequently, this algorithm can recognize the styles and shapes of regular script and seal script in an entire calligraphy work at single-character recognition rates of 91.57% and 81.70%, demonstrating its practicability.

    Reference
    Related
    Cited by
Get Citation

许嘉谕,林楚烨,陈志涛,邓卓然,潘家辉,梁艳.基于深度学习的手写书法字体识别算法.计算机系统应用,2021,30(2):213-218

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:June 25,2020
  • Revised:July 27,2020
  • Adopted:
  • Online: January 29,2021
  • Published:
Article QR Code
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063