Image Theft Detection with Self-Organising Maps

Authors:
Philip Prentis;Mats Sjöberg;Markus Koskela;Jorma Laaksonen
Affiliations:
Czech Technical University in Prague, Helsinki University of Technology,;Czech Technical University in Prague, Helsinki University of Technology,;Czech Technical University in Prague, Helsinki University of Technology,;Czech Technical University in Prague, Helsinki University of Technology,
Venue:
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Year:
2009

Citing 4
Cited 0

PicSOM—content-based image retrieval with self-organizing maps

Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Self-Organizing Maps

Self-Organizing Maps
Zero Knowledge Watermark Detection

IH '99 Proceedings of the Third International Workshop on Information Hiding
PicSOM-self-organizing image retrieval with MPEG-7 content descriptors

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper an application of the TS-SOM variant of the self-organising map algorithm on the problem of copyright theft detection for bitmap images is shown. The algorithm facilitates the location of originals of copied, damaged or modified images within a database of hundreds of thousands of stock images. The method is shown to outperform binary decision tree indexing with invariant frame detection.