• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2010, Vol. 32 ›› Issue (11): 66-70.doi: 10.3969/j.issn.1007130X.2010.

• 论文 • 上一篇    下一篇

基于图像分析的军队标号绘制自动化测试方法研究

赵小琴,王玉玫   

  1. (华北计算技术研究所,北京 100083)
  • 收稿日期:2009-11-15 修回日期:2010-01-25 出版日期:2010-11-25 发布日期:2010-11-25
  • 通讯作者: 赵小琴
  • 作者简介:赵小琴(1984),女, 山西阳泉人,硕士生,研究方向为软件自动化测试;王玉玫,研究员,研究方向为计算机图形学和分布式应用系统。

On a Automation Testing Method for Military Symbol Plotting Based on Image Analysis

ZHAO Xiaoqin,WANG Yumei   

  1. (Institute of Northern Computing Technique,Beijing 100083,China)
  • Received:2009-11-15 Revised:2010-01-25 Online:2010-11-25 Published:2010-11-25

摘要: 军队标号作为军用态势图中基本的图形元素,在军用指挥控制系统中具有重要的意义。目前对军标符号的测试大都采用手工测试的方法,测试效率较低。本文针对这个问题,设计并实现了对军标符号的自动化测试。首先,本文实现了军标符号的自动标绘;然后采用图像分析中的形态学膨胀方法、角点检测技术以及图像二值化分析方法,着重对军标符号的线宽、柔化、颜色三个常用属性的测试进行研究和设计;最后根据测试结果自动生成测试报告。实验结果表明,本文为验证军标符号绘制的正确性提供了一种可行、有效的自动化测试方法,使图形图像分析在自动化测试领域有了新的应用。

关键词: 军标绘制, 自动化测试, 图像二值化, 二值膨胀, 角点检测

Abstract: Military symbol is a basic graphic element in the situation picture, which has an important meaning in military command and control systems. The current military symbol testing mostly adopts manual testing methods, which has low efficiency. This paper focuses on this issue, designs and implements an automated testing method for military symbols. Firstly, it achieves the target of automatic military symbol plotting; and then mainly uses the technologies of morphological expansion, corner detection and image binarization for image analysis, which gives a design and implementation on the military symbol testing for three commonly used attributes of line width, softening and color. Finally, according to the testing results ,it automatically builds the testing reports. The experimental results show that, this paper provides a feasible, effective automated testing way for the validation of military symbol correct drawing, and implements a new applicable scene for image analysis in the automated testing domain.

Key words: military symbol plotting;automation testing;image binarization;binary expansion;corner detection