北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2016, Vol. 39 ›› Issue (3): 49-53.doi: 10.13190/j.jbupt.2016.03.008

• 论文 • 上一篇    下一篇

基于模板匹配的新闻图像字幕行切分算法

王志衡, 郭超, 刘红敏   

  1. 河南理工大学 计算机科学与技术学院, 河南 焦作 454003
  • 收稿日期:2015-09-24 出版日期:2016-06-28 发布日期:2016-06-27
  • 作者简介:王志衡(1983-),男,副教授;刘红敏(1982-),女,副教授,E-mail:hongminliu@hpu.edu.cn.
  • 基金资助:

    国家自然科学基金项目(61572173,61472119,61472373,61272394);河南省高校创新科技人才项目(13HASTIT039);河南理工大学创新型科研团队项目(T2014-3);河南理工大学杰出青年基金项目(J2013-2)

News Image Caption Line Segmentation Algorithm Based on Template Matching

WANG Zhi-heng, GUO Chao, LIU Hong-min   

  1. College of Computer Science and Technology, Henan Polytechnic University, Henan Jiaozuo 454000, China
  • Received:2015-09-24 Online:2016-06-28 Published:2016-06-27

摘要:

针对新闻图像中水平字幕行的字符切分问题,为了克服已有基于单字符切分方法造成的字符分裂问题,利用字幕行中字符的分布规律构造了响应函数,从而将字符切分问题转变为响应函数的最优值问题,最后基于优化结果进行字符切分.该算法主要包括两部分:首先,利用垂直投影直方图确定单个字符的粗略宽度,并根据该值构造一个可变长模板;然后,构造模板响应函数,根据不同长度模板的最优响应函数值确定单个字符的左右边界位置;最后输出切分结果.实验结果表明,对于粘连/非粘连字符图像,该算法均能获得较好的实验结果.

关键词: 新闻图像, 标题字幕, 模板匹配, 字符切分

Abstract:

The research on the character segmentation of the horizontal caption line in news images was made in this article. In order to overcome the character splitting problem caused by existing single character based segmentation methods, a response function was proposed based on character distribution. The character segmentation problem is converted into an optimal problem, and the character segmentation can be attained by turning to the optimal result. The algorithm mainly contains two parts:First, the rough width of a single character is determined based on the vertical projection histogram, which is utilized to construct a variable length template; Then, the template response function is constructed and the left/right boundary position of a single character is determined by the optimal value of the response function of different length templates; Last, output the segmentation results. Experimental results show that the proposed method can obtain satisfactory results for adhesion/non-adhesion character images.

Key words: news images, captions, template matching, character segmentation

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