使用Sobel算子和OCR的垃圾邮件多重过滤器

Peng Wan, M. Uehara
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引用次数: 5

摘要

垃圾邮件不仅浪费收件人的时间,而且还会传播有害信息和病毒。为了避免垃圾邮件过滤器,垃圾邮件发送者通常发送图像而不是文本。传统的图像垃圾过滤器在扫描文档和照片方面存在弱点。然而,为了传递信息,文本总是被用于图像垃圾中。因此,在本研究中,我们通过字母和图像的配置对邮件图像进行分类。我们提出了一种垃圾邮件检测方法,该方法使用Sobel算子进行边缘检测,并使用Sobel算子和OCR进行多重过滤器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple Filters of Spam Using Sobel Operators and OCR
Spam mail (junk email) is not only a waste of time for the recipients but can also spread harmful messages and viruses. To avoid spam filters, spam senders usually send images instead of text. Traditional image spam filters have weaknesses in scanning documents and photographs. However, to transmit information, text is always used in image spam. Therefore, in this study, we classify mail images by the configuration of letters and images. We propose a spam detection method that uses Sobel operators for edge detection and a multiple filter using Sobel operators and OCR.
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