Abstract
Social networking sites are increasingly being used as the source for paedophiles to search for, download and exchange child exploitation images. Law Enforcement Agencies (LEAs) around the world face a difficult challenge to combat technologically-savvy paedophiles. In this paper, we propose a framework for detecting images containing children's pictures in different poses, with the ultimate view of identifying and classifying images as corresponding to the COPINE scale. To achieve the goal of automatic detection, we present a novel stochastic vision model based on a Markov Random Fields (MRF) prior, which will employ a skin model and human affine-invariant geometric descriptor to detect and identify skin regions containing pornographic contexts.
Original language | English |
---|---|
Pages (from-to) | 51-58 |
Number of pages | 8 |
Journal | Information Security Technical Report |
Volume | 16 |
Issue number | 2 |
DOIs | |
Publication status | Published - May 2011 |
Externally published | Yes |
Keywords
- Child exploitation
- Forensics
- MRF models
- Skin models