Camera model identification is of interest for many applications. In-camera processes, specific of each model, leave traces that can be captured by features designed ad hoc, and used for reliable classification. In this work we investigate on the use of blind features based on the analysis of image residuals. In particular, features are extracted locally based on co-occurrence matrices of selected neighbors and then used to train an SVM classifier. Experiments on the well-known Dresden database show this approach to provide state-of-the-art performances.

Evaluation of Residual-Based Local Features for Camera Model Identification / Marra, Francesco; Poggi, Giovanni; Sansone, Carlo; Verdoliva, Luisa. - 9281:(2015), pp. 11-18. (Intervento presentato al convegno ICIAP 2015 International Workshops tenutosi a Genoa, Italy nel September 7-8) [10.1007/978-3-319-23222-5_2].

Evaluation of Residual-Based Local Features for Camera Model Identification

MARRA, FRANCESCO;POGGI, GIOVANNI;SANSONE, CARLO;VERDOLIVA, LUISA
2015

Abstract

Camera model identification is of interest for many applications. In-camera processes, specific of each model, leave traces that can be captured by features designed ad hoc, and used for reliable classification. In this work we investigate on the use of blind features based on the analysis of image residuals. In particular, features are extracted locally based on co-occurrence matrices of selected neighbors and then used to train an SVM classifier. Experiments on the well-known Dresden database show this approach to provide state-of-the-art performances.
2015
978-3-319-23221-8
978-3-319-23222-5
978-3-319-23221-8
978-3-319-23222-5
Evaluation of Residual-Based Local Features for Camera Model Identification / Marra, Francesco; Poggi, Giovanni; Sansone, Carlo; Verdoliva, Luisa. - 9281:(2015), pp. 11-18. (Intervento presentato al convegno ICIAP 2015 International Workshops tenutosi a Genoa, Italy nel September 7-8) [10.1007/978-3-319-23222-5_2].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/611557
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