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Automatic GUI Test by Using SIFT Matching
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作者 Xiaoxin Fang Bin Sheng +2 位作者 Ping Li Dan Wu Enhua Wu 《China Communications》 SCIE CSCD 2016年第9期227-236,共10页
In software development process,the last step is usually the Graphic User Interface(GUI) test,which is part of the final user experience(UE) test.Traditionally,there exist some GUI test tools in the market,such as Abb... In software development process,the last step is usually the Graphic User Interface(GUI) test,which is part of the final user experience(UE) test.Traditionally,there exist some GUI test tools in the market,such as Abbot Java GUI Test Framework and Pounder,in which testers pre-configure in the script all desired actions and instructions for the computer,nonetheless requiring too much of invariance of GUI environment;and they require reconfiguration in case of GUI changes,therefore still to be done mostly manually and hard for non-programmer testers to.Consequently,we proposed GUI tests by image recognition to automate the last process;we managed to innovate upon current algorithms such as SIFT and Random Fern,from which we develop the new algorithm scheme retrieving most efficient feature and dispelling inefficient part of each algorithm.Computers then apply the algorithm,to search for target patterns themselves and take subsequent actions such as manual mouse,keyboard and screen I/O automatically to test the GUI without any manual instructions.Test results showed that the proposed approach can accelerate GUI test largely compared to current benchmarks. 展开更多
关键词 测试工具 图形用户界面 软件开发过程 计算机应用 匹配 筛选 gui 测试自动化
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SIFT和改进的RANSAC算法在图像配准中的应用 被引量:25
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作者 罗文超 刘国栋 杨海燕 《计算机工程与应用》 CSCD 2013年第15期147-149,156,共4页
在机器人视觉系统中运用SIFT描述子对现实世界中的目标进行识别,这一研究已经取得了很大的进步。运用SIFT生成的图像特征向量的性能十分稳定,对旋转、缩放、平移是保持不变性的,对一定程度目标遮挡、光照变化、视点变化、杂物场景和噪... 在机器人视觉系统中运用SIFT描述子对现实世界中的目标进行识别,这一研究已经取得了很大的进步。运用SIFT生成的图像特征向量的性能十分稳定,对旋转、缩放、平移是保持不变性的,对一定程度目标遮挡、光照变化、视点变化、杂物场景和噪声等也能保持很好的不变性。RANSAC算法早就已经是计算机视觉领域常用的一个进行矫正的标准方法,在标准的RANSAC算法基础上加入了假设评价,改进为R-RANSAC(The Randomized RANSAC)算法。对这两个方面进行论述,运用SIFT(尺度不变特征变换)算法对双目机器人的两幅视觉图像进行匹配,采用带SPRT的R-RANSAC改进算法对匹配过程进行优化,尽可能在短的时间里完成匹配矫正,进而加速整个配准的时间。 展开更多
关键词 尺度不变特征变换(sift)描述子 图像匹配 图像配准 随机抽样一致性 顺序概率比测试
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