基于图像匹配算法的自动测试系统研究

Zhenhao Wu, Chunjie Xu, Shitao Zhao
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引用次数: 0

摘要

传统的系统测试采用图形界面,测试结果由人工确定。随着当前工业领域对测试软件系统精度的要求越来越高,传统的人工测试存在成本高、精度低、效率低等问题。然后提出了一种基于图像匹配算法的自动测试系统来模拟人工自动测试结果。首先,研究了自动测试系统的体系结构,降低了测试成本;然后,针对目标图像的复杂性,采用模板匹配算法和ORB算法进行自动选择,提高了匹配率和精度。最后,构建了一种基于感知哈希算法的图像相似度计算算法,将测试精度和效率提高了两倍。实验结果表明,该方法的精度达到97%,满足工业领域的精度要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on automatic test system based on image matching algorithm
The traditional test of the system using graphical interface determines the test results by manual. With the higher accuracy requirements of the test software system in current industrial domain, the traditional manual testing has the problems of high costs, low accuracy and efficiency. Then an automatic test system based on image matching algorithm is proposed to simulate manual automatic test result. Firstly, the architecture of automatic test system is researched, which reduces the test cost. Then, an automatically selected method by template matching algorithm and ORB algorithm for the complexity of the target images, which improves the matching rate and accuracy. Finally, an image similarity calculation algorithm based on perceptual hash algorithm is built, which improves the test accuracy and efficiency twice. The experimental results show that the accuracy achieved to 97%, which meets the accuracy requirements for the industrial field.
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