Visual Feature-Based Image Spam Filters
Advances in information security, privacy, and ethics book series · 2017
This chapter provides the details of visual feature based image spam filters, a literature review on these spam filters and their limitations. These methods are generally computationally efficient and exhibits more accuracy in presence of various noises compared to OCR based detection schemes, as they do not include any text recognition stage (Lamia et al., 2012). Previously discussed near-duplicate spam detection methods are likely to perform well in abstracting base templates, when given enough examples of various spam templates in use (Mehta et al., 2008). However, the generalization ability of these methods will be limited. Visual feature based spam detection methods are generally built using different high level and/or low level image features (refer Chapter 3 of this book) related to color, shape, texture characteristics of spam images; hence they have more generalization capability (Lamia et al., 2012). Mostly; these techniques exploit the text intensive and noisy nature of spam images.