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


KIPS Transactions on Software and Data Engineering, Vol. 11, No. 2, pp. 87-92, Feb. 2022
https://doi.org/10.3745/KTSDE.2022.11.2.87,   PDF Download:
Keywords: Application Test, Deep Learning, Image matching, Feature matching, Image Compare
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.


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Cite this article
[IEEE Style]
C. Hye-Won, J. Min-Seok, H. Sung-Soo, J. Chang-Sung, "Image-Based Application Testing Method Using Faster D2-Net for Identification of the Same Image," KIPS Transactions on Software and Data Engineering, vol. 11, no. 2, pp. 87-92, 2022. DOI: https://doi.org/10.3745/KTSDE.2022.11.2.87.

[ACM Style]
Chun Hye-Won, Jo Min-Seok, Han Sung-Soo, and Jeong Chang-Sung. 2022. Image-Based Application Testing Method Using Faster D2-Net for Identification of the Same Image. KIPS Transactions on Software and Data Engineering, 11, 2, (2022), 87-92. DOI: https://doi.org/10.3745/KTSDE.2022.11.2.87.