Skew Detection for Chinese Handwriting by Horizontal Stroke Histogram

Tong-Hua Su, Tian-Wen Zhang, Hu-Jie Huang, Yu Zhou
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引用次数: 22

Abstract

This paper proposes a skew detection method for real Chinese handwritten documents. After analyzing the characteristics of Chinese characters, it utilizes the horizontal stroke histogram. Its accuracy, ability to increase the recall rate of text line separation, and CPU time consuming are investigated using 853 real Chinese handwritten documents. The results show that: 1) the method can identify 98.83% of the skew angles within one degree, with an improvement of 8.44% than Wigner-Ville distribution (WVD) method; 2) when incorporated into text line separation, the recall rate has an improvement of 2.54% than WVD method; 3) the method only consumes one-twentieth of WVD method on the same test environment.
基于水平笔画直方图的汉字书写歪斜检测
提出了一种针对真实中文手写文档的倾斜检测方法。在分析了汉字的特点后,采用了横画直方图。以853份真实中文手写文档为例,考察了该方法的准确率、提高文本行分离查全率的能力和CPU耗时。结果表明:1)该方法能在1度内识别出98.83%的倾斜角,比WVD方法提高了8.44%;2)结合文本行分离,召回率比WVD方法提高了2.54%;3)在相同的测试环境下,该方法的能耗仅为WVD法的二十分之一。
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