Embedded-Text Detection and Its Application to Anti-Spam Filtering
نویسندگان
چکیده
Embedded-Text Detection and Its Application to Anti-Spam Filtering Ching-Tung Wu Embedded-text in images usually carry important messages about the content. In the past, several algorithms have been proposed to detect text boxes in video frames. Previous work often followed a multi-step framework using a combination of image-analysis and machine-learning techniques. In this work, we propose a unified embedded-text detection framework to efficiently and accurately locate text boxes particularly in web and email images. We approach the embeddedtext problem from the angle of object detection. We define position-independent features to capture the essence of characters and a smart-scan algorithm to trace text lines using their spatial and geometrical properties. We also propose a novel anti-spam system which utilizes visual clues, including the embedded-text information. The experimental results demonstrate the effectiveness of the proposed embedded-text detection framework and the anti-spam filtering system. Professor Kwang-Ting Cheng Thesis Committee Chair iv
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