-grayscale digital image.
-
-
-\subsection{Adaptive Embedding Rate}
-
-Two strategies have been developed in our scheme, depending on the embedding rate that is either \emph{adaptive} or \emph{fixed}.
-
-In the former the embedding rate depends on the number of edge pixels.
-The higher it is, the larger is the message length that can be inserted.
-Practically, a set of edge pixels is computed according to the
-Canny algorithm with an high threshold.
-The message length is thus defined to be the half of this set cardinality.
-In this strategy, two methods are thus applied to extract bits that
-are modified. The first one is a direct application of the STC algorithm.
-This method is further referred as \emph{adaptive+STC}.
-The second one randomly choose the subset of pixels to modify by
-applying the BBS PRNG again. This method is denoted \emph{adaptive+sample}.
-Notice that the rate between
-available bits and bit message length is always equal to 2.
-This constraint is indeed induced by the fact that the efficiency
-of the STC algorithm is unsatisfactory under that threshold.
-On our experiments and with the adaptive scheme,
-the average size of the message that can be embedded is 16445.
-Its corresponds to an average payload of 6.35\%.
+grayscale digital image in a RAW format.
+We restrict experiments to
+this set of cover images since this paper is more focused on
+the methodology than benchmarking.
+We use the matrices given in table~\ref{table:matrices:H}
+as introduced in~\cite{}, since these ones have experimentally
+be proven to have the best modification efficiency.
+
+\begin{table}
+$$
+\begin{array}{|l|l|}
+\textrm{rate} & \textrm{matrix generators} \\
+$\frac{1}{2} & \{71,109\}
+$\frac{1}{3} & \{95, 101, 121\}
+$\frac{1}{4} & \{81, 95, 107, 121\}
+$\frac{1}{5} & \{75, 95, 97, 105, 117\}
+$\frac{1}{6} & \{73, 83, 95, 103, 109, 123\}
+$\frac{1}{7} & \{69, 77, 93, 107, 111, 115, 121\}
+$\frac{1}{8} & \{69, 79, 81, 89, 93, 99, 107, 119\}
+$\frac{1}{9} & \{69, 79, 81, 89, 93, 99, 107, 119, 125]
+
