By Topic

Image Spam Filtering Using Visual Information

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)

We address the problem of recognizing the so-called image spam, which consists in embedding the spam message into attached images to defeat techniques based on the analysis of e-mails' body text, and in using content obscuring techniques to defeat OCR tools. We propose an approach to recognize image spam based on detecting the presence of content obscuring techniques, and describe a possible implementation based on two low-level image features aimed at detecting obscuring techniques whose consequence is to compromise the OCR effectiveness resulting in character breaking or merging, or in the presence of noise interfering with characters in the binarized image. A preliminary experimental investigation of this approach is reported on a personal data set of spam images.

Published in:

Image Analysis and Processing, 2007. ICIAP 2007. 14th International Conference on

Date of Conference:

10-14 Sept. 2007