From c3a95ed8fc5f859794c70ff978205770c6df81a3 Mon Sep 17 00:00:00 2001
From: Jordi Inglada <jordi.inglada@orfeo-toolbox.org>
Date: Wed, 5 Jul 2006 15:03:48 +0000
Subject: [PATCH] Exemples morpho math
---
SoftwareGuide/Examples/CMakeLists.txt | 2 ++
SoftwareGuide/Latex/Filtering.tex | 36 +++++++++++++--------------
2 files changed, 20 insertions(+), 18 deletions(-)
diff --git a/SoftwareGuide/Examples/CMakeLists.txt b/SoftwareGuide/Examples/CMakeLists.txt
index ab11ceb84f..0b3b02338d 100644
--- a/SoftwareGuide/Examples/CMakeLists.txt
+++ b/SoftwareGuide/Examples/CMakeLists.txt
@@ -196,6 +196,8 @@ SET( OTB_EXAMPLES_SRCS
${OTB_SOURCE_DIR}/Examples/Filtering/DiscreteGaussianImageFilter.cxx
${OTB_SOURCE_DIR}/Examples/Filtering/GradientAnisotropicDiffusionImageFilter.cxx
${OTB_SOURCE_DIR}/Examples/Filtering/DanielssonDistanceMapImageFilter.cxx
+ ${OTB_SOURCE_DIR}/Examples/Filtering/MathematicalMorphologyBinaryFilters.cxx
+ ${OTB_SOURCE_DIR}/Examples/Filtering/MathematicalMorphologyGrayscaleFilters.cxx
${OTB_SOURCE_DIR}/Examples/BasicFilters/LeeImageFilter.cxx
${OTB_SOURCE_DIR}/Examples/FeatureExtraction/AlignmentsExample.cxx
${OTB_SOURCE_DIR}/Examples/FeatureExtraction/RatioLineDetectorExample.cxx
diff --git a/SoftwareGuide/Latex/Filtering.tex b/SoftwareGuide/Latex/Filtering.tex
index bac4df1490..3e692165c2 100644
--- a/SoftwareGuide/Latex/Filtering.tex
+++ b/SoftwareGuide/Latex/Filtering.tex
@@ -169,30 +169,30 @@ advantage of this construction. (See Chapter
\fi
-%% \subsection{Mathematical Morphology}
-%% \label{sec:MathematicalMorphology}
+\subsection{Mathematical Morphology}
+\label{sec:MathematicalMorphology}
-%% Mathematical morphology has proved to be a powerful resource for image
-%% processing and analysis \cite{Serra1982}. ITK implements mathematical
-%% morphology filters using NeighborhoodIterators and
-%% \doxygen{itk}{NeighborhoodOperator}s. The toolkit contains two types of image
-%% morphology algorithms, filters that operate on binary images and filters that
-%% operate on grayscale images.
+Mathematical morphology has proved to be a powerful resource for image
+processing and analysis \cite{Serra1982}. ITK implements mathematical
+morphology filters using NeighborhoodIterators and
+\doxygen{itk}{NeighborhoodOperator}s. The toolkit contains two types of image
+morphology algorithms, filters that operate on binary images and filters that
+operate on grayscale images.
-%% \subsubsection{Binary Filters}
-%% \label{sec:MathematicalMorphologyBinaryFilters}
+\subsubsection{Binary Filters}
+\label{sec:MathematicalMorphologyBinaryFilters}
-%% \ifitkFullVersion
-%% %\input{MathematicalMorphologyBinaryFilters.tex}
-%% \fi
+\ifitkFullVersion
+\input{MathematicalMorphologyBinaryFilters.tex}
+\fi
-%% \subsubsection{Grayscale Filters}
-%% \label{sec:MathematicalMorphologyGrayscaleFilters}
+\subsubsection{Grayscale Filters}
+\label{sec:MathematicalMorphologyGrayscaleFilters}
-%% \ifitkFullVersion
-%% %\input{MathematicalMorphologyGrayscaleFilters.tex}
-%% \fi
+\ifitkFullVersion
+\input{MathematicalMorphologyGrayscaleFilters.tex}
+\fi
%% \subsection{Voting Filters}
--
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