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http://dx.doi.org/10.5909/JBE.2014.19.5.578

Subimage Detection of Window Image Using AdaBoost  

Gil, Jong In (Dept. of Computer and Communications Engineering, Kangwon National University)
Kim, Manbae (Dept. of Computer and Communications Engineering, Kangwon National University)
Publication Information
Journal of Broadcast Engineering / v.19, no.5, 2014 , pp. 578-589 More about this Journal
Abstract
Window image is displayed through a monitor screen when we execute the application programs on the computer. This includes webpage, video player and a number of applications. The webpage delivers a variety of information by various types in comparison with other application. Unlike a natural image captured from a camera, the window image like a webpage includes diverse components such as text, logo, icon, subimage and so on. Each component delivers various types of information to users. However, the components with different characteristic need to be divided locally, because text and image are served by various type. In this paper, we divide window images into many sub blocks, and classify each divided region into background, text and subimage. The detected subimages can be applied into 2D-to-3D conversion, image retrieval, image browsing and so forth. There are many subimage classification methods. In this paper, we utilize AdaBoost for verifying that the machine learning-based algorithm can be efficient for subimage detection. In the experiment, we showed that the subimage detection ratio is 93.4 % and false alarm is 13 %.
Keywords
Subimage detection; Projection Profile Cutting; Local Binary Patterns; AdaBoost;
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