Authors:
Viktor de Boer
1
;
Maarten van Someren
1
and
Tiberiu Lupascu
2
Affiliations:
1
Informatics Institute, Universiteit van Amsterdam, Netherlands
;
2
Euro IT&C B.V., Netherlands
Keyword(s):
Web design, Computer vision, Image analysis, Machine learning.
Related
Ontology
Subjects/Areas/Topics:
Multimedia and User Interfaces
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
Abstract:
To automatically classify and process web pages, current systems use the textual content of those pages, including both the displayed content and the underlying (HTML) code. However, a very important feature of a web page is its visual appearance. In this paper, we show that using generic visual features we can classify the web pages for several different types of tasks. The features used in this document are simple color and edge histograms, Gabor and texture features. These were extracted using an off-the-shelf visual feature extraction method. In three experiments, we classify web pages by their aesthetic value, their recency and the type of website. Results show that these simple, global visual features already produce good classification results. We also introduce an online tool that uses the trained classifiers to assess new web pages.