\chapter{A SIFT-based forensic method for copy-move detection}\label{chap:forensic}
{

\begin{quote}
\textit{One of the principal problem image forensics has to deal with is determining if a particular image is authentic or not. This task is very important in all those fields where is crucial to use such digital content as evidence like, for instance, in a court of law. To carry out such forensic analysis various technological instruments have been developed in literature. Many of them try to reveal if some modifications have been performed thus assessing that something of suspect could have been made, other ones search for comprehending what has happened and possibly which relations there are with other linked photos. In this chapter the problem of detecting if a feigned image has been created is investigated; in particular, attention has been paid to the case in which an area of an image is copied and then pasted onto another zone to make a duplication or to cancel something that was awkward.
To detect such modifications we propose a new methodology based on SIFT features. Our method allows both to understand if a copy-move attack has occurred and which are the image points involved, and, furthermore, to recover which has been the geometric transformation happened to perform cloning.
\footnote{A preliminary version of the work presented in this chapter has been published as \dquote{Geometric tampering estimation by means of a SIFT-based forensic analysis} in \textit{Proc.~of IEEE Int'l Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2010},~\cite{ameriniICASSP} and submitted to IEEE Trans.~on Information Forensics and Security (TIFS).}
}
\end{quote}


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\section{Introduction}\label{sec:intro5}


%-------------------------------------------------------------------------
\section{SIFT Features for Image Forensics}\label{sec:two}

\subsection{Our contribution}\label{sec:contribution5}


%-------------------------------------------------------------------------
\section{The proposed method}\label{sec:three}

\subsection{SIFT features extraction and multiple keypoint matching}

\subsection{Clustering and forgeries detection}\label{sec:cluster}

\subsection{Geometric transformation estimation}\label{ssec:three}


% -------------------------------------------------------------------------
\section{Experimental results}\label{sec:four}

\subsection{Settings for forgery detection}\label{ssec:four1}

\subsection{Test on multiple copied regions}

\subsection{Test on a large dataset}

\subsection{Image splicing}


% -------------------------------------------------------------------------
\section{Conclusion}\label{sec:five}

}