What question did this study set out to answer?

The study aims to develop a scalable system for detecting adult-oriented images on the Internet.

January 1, 2006Open Access

Large Scale Image-Based Adult-Content Filtering

Key Points

The study aims to develop a scalable system for detecting adult-oriented images on the Internet.
Implemented a system for adult-content image detection using face detection techniques.
Computed summary features for each image to enhance classification accuracy.
Utilized a support vector machine for classification of images into adult or non-adult categories.
A significant fraction of pornographic images was successfully detected using the system.
The approach shows potential applicability in large-scale search engines.

Abstract

Abstract: As more people start using the Internet and more content is placed online, the chances that individuals will encounter inappropriate or unwanted adult-oriented content increases. This paper presents a practical and scalable method to efficiently detect many adult-content images, specifically pornographic images. We currently use this system in a search engine that covers a large fraction of the images on the WWW. For each image, face detection is applied and a number of summary features are computed; the results are then fed to a support vector machine for classification. The results show that a significant fraction of adult-content images can be detected. 1

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