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http://dx.doi.org/10.5762/KAIS.2020.21.2.160

Automatic Detection of Dissimilar Regions through Multiple Feature Analysis  

Jang, Seok-Woo (Department of Software, Anyang University)
Jung, Myunghee (Department of Software, Anyang University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.21, no.2, 2020 , pp. 160-166 More about this Journal
Abstract
As mobile-based hardware technology develops, many kinds of applications are also being developed. In addition, there is an increasing demand to automatically check that the interface of these applications works correctly. In this paper, we describe a method for accurately detecting faulty images from applications by comparing major characteristics from input color images. For this purpose, our method first extracts major characteristics of the input image, then calculates the differences in the extracted major features, and decides if the test image is a normal image or a faulty image dissimilar to the reference image. Experiment results show that the suggested approach robustly determines similar and dissimilar images by comparing major characteristics from input color images. The suggested method is expected to be useful in many real application areas related to computer vision, like video indexing, object detection and tracking, image surveillance, and so on.
Keywords
Image Similarity; Accuracy Measure; Feature Acquisition; Difference; Color Cmage;
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Times Cited By KSCI : 6  (Citation Analysis)
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