Image Replica Detection based on Binary Support Vector Classifier

• Publication date: 2005

In this paper, we present a system for image replica detection. More specifically, the technique is based on the extraction of 162 features corresponding to texture, color and gray-level characteristics. These features are then weighted and statistically normalized. To improve training and performances, the features space dimensionality is reduced. Lastly, a decision function is generated to classify the test image as replica or non-replica of a given reference image. Experimental results show the effectiveness of the proposed system. Target applications include search for copyright infringement (e.g. variations of copyrighted images) and illicit content (e.g. pedophile images).

Note: ITS

Keywords: copyright infringement ; dimensionality reduction ; features extraction ; image replica detection ; image search ; LTS1 ; support vector machine

Reference

• LTS-REPORT-2005-020

Record created on 2006-06-14, modified on 2012-03-21