计算机与现代化 ›› 2014, Vol. 0 ›› Issue (1): 96-99,120.

• 算法设计与分析 • 上一篇    下一篇

基于神经网络的汉字质量量化评价模型

  

  1. 同济大学电子与信息工程学院,上海201804
  • 收稿日期:2013-11-14 出版日期:2014-01-20 发布日期:2014-02-10
  • 作者简介: 耿晓艳(1988-),女,内蒙古鄂尔多斯人,同济大学电子与信息工程学院硕士研究生,研究方向:模式识别与智能系统; 许维胜(1966-),男,教授,博士生导师,博士,研究方向:智能自动化理论与工程; 吴继伟(1974-),男,讲师,博士,研究方向:过程控制与计算机控制。
  • 基金资助:
    上海市科学技术委员会科研计划项目(11dz1505202)

Quality Evaluation Model of Chinese Characters Based on Neural Network

  1. College of Electronics and Information, Tongji University, Shanghai 201804, China
  • Received:2013-11-14 Online:2014-01-20 Published:2014-02-10

摘要: 针对传统的汉字字库制作技术需要人工对构字结果进行大量操作,提出利用汉字的属性特征,对构字结果实现质量评价的方法。该方法首先采用图像处理技术提取能够反映汉字标准书写规则的属性,从而将汉字质量的评价准则量化;然后通过改进的三层BP神经网络进行训练,建立汉字品质的评价模型,为字体的调整提供依据,降低字库制作过程中的人工投入。

关键词:  , 属性, 质量评价, 图像处理, 量化, BP神经网络

Abstract: Traditional making technology of Chinese character database requires a large number of manual operations in the character-formation results. In order to solve this defect, a method of achieving quality evaluation for the character-formation results is proposed by using attributes of Chinese characters. First, this paper extracts the attributes which could reflect the standard writing rules of Chinese characters through image processing technology, to quantify the evaluation criteria of Chinese characters, and then, models the font quality evaluation making use of the improved three-layer BP neural network, which would provide basis for adjustment of the font and reduce the human input in the process of character making.

Key words:  attributes, quality evaluation, image processing, quantization, BP neural network