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http://dx.doi.org/10.3745/KTSDE.2022.11.2.87

Image-Based Application Testing Method Using Faster D2-Net for Identification of the Same Image  

Chun, Hye-Won (고려대학교 전기전자공학과)
Jo, Min-Seok (고려대학교 전기전자공학과)
Han, Sung-Soo (강원대학교 자유전공학부)
Jeong, Chang-Sung (고려대학교 전자공학과)
Publication Information
KIPS Transactions on Software and Data Engineering / v.11, no.2, 2022 , pp. 87-92 More about this Journal
Abstract
Image-based application testing proposes an application testing method via image structure comparison. This test method allows testing on various devices without relying on various types of device operating systems or GUI. Traditional studies required the creation of a tester for each variant in the existing case, because it differs from the correct image for operating system changes, screen animation execution, and resolution changes. The study determined that the screen is the same for variations. The tester compares the underlying structure of the objects in the two images and extracts the regions in which the differences exist in the images, and compares image similarity as characteristic points of the Faster D2-Net. The development of the Faster D2-Net reduced the number of operations and spatial losses compared to the D2-Net, making it suitable for extracting features from application images and reducing test performance time.
Keywords
Application Test; Deep Learning; Image Matching; Feature Matching; Image Compare;
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