On Detection of Advertising Images
Dongfang Li, Bin Wang, Zhiwei Li, Nenghai Yu, Mingjing Li · 2007
Online advertising has enjoyed exponential growth in recent years, and many advertisements appear in the form of images. Although it makes considerable profit, these advertisements tend to disturb the Internet surfing of normal users. Moreover, they always bring extra burden in indexing to commercial image search engines. Therefore, it is necessary to automatically detect those advertising images on the Web. In this paper, a classification based approach is proposed for advertising image detection, in which comprehensive features are exploited and effectively combined. Those features include visual content, link, text and visual layout in hosting Web pages. Promising experimental results are obtained on images collected from about 480 Web sites.