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ICDAR
2005
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Image Analysis for Efficient Categorization of Image-based Spam E-mail

9 years 5 months ago
Image Analysis for Efficient Categorization of Image-based Spam E-mail
To circumvent prevalent text-based anti-spam filters, spammers have begun embedding the advertisement text in images. Analogously, proprietary information (such as source code) may be communicated as screenshots to defeat text-based monitoring of outbound e-mail. The proposed method separates spam images from other common categories of e-mail images based on extracted overlay text and color features. No expensive OCR processing is necessary. Our method works robustly in spite of complex backgrounds, compression artifacts, and a wide variety of formats and fonts of overlaid spam text. It is also demonstrated successfully to detect screenshots in outbound e-mail.
Hrishikesh Aradhye, Gregory K. Myers, James A. Her
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICDAR
Authors Hrishikesh Aradhye, Gregory K. Myers, James A. Herson
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