# HG changeset patch
# User Xavier Glorot <glorotxa@iro.umontreal.ca>
# Date 1272479730 14400
# Node ID 0580b310dadbfe6220608857f9b0627d3ef2a23b
# Parent  fe2e2964e7a381a4dcf9cfebe62bd8607ed71371# Parent  a11274742088abb7ac3b45b7fb0f3b32d555e091
merge

diff -r a11274742088 -r 0580b310dadb writeup/specials.bib
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/writeup/specials.bib	Wed Apr 28 14:35:30 2010 -0400
@@ -0,0 +1,15 @@
+@Book{Serra82,
+  author =       "J. Serra",
+  title =        "Image Analysis and Mathematical Morphology",
+  publisher =    "Academic Press",
+  year =         "1982",
+} 
+@Article{Haralick87,
+  author =       "R. M. Haralick and S. R. Sternberg and X. Zhuang",
+  title =        "Image analysis using mathematical morphology",
+  journal =      "IEEE Trans. Pattern. Anal. Mach. Intel.",
+  volume =       "9",
+  number =       "4",
+  pages =        "532-550",
+  year =         "1987",
+}
diff -r a11274742088 -r 0580b310dadb writeup/techreport.tex
--- a/writeup/techreport.tex	Wed Apr 28 14:28:32 2010 -0400
+++ b/writeup/techreport.tex	Wed Apr 28 14:35:30 2010 -0400
@@ -72,10 +72,27 @@
 
 \section{Perturbation and Transformation of Character Images}
 
+\subsection{Adding Slant}
+In order to mimic a slant effect, we simply shift each row of the image proportionnaly to its height.
+The coefficient is randomly sampled according to the complexity level and can be negatif or positif with equal probability.
+
+\subsection{Changing Thickness}
+To change the thickness of the characters we used morpholigical operators: dilation and erosion~\cite{Haralick87,Serra82}.
+The basic idea of such transform is, for each pixel, to multiply in the element-wise manner its neighbourhood with a matrix called the structuring element.
+Then for dilation we remplace the pixel value by the maximum of the result, or the minimum for erosion.
+This will dilate or erode objects in the image, the strength of the transform only depends on the structuring element.
+We used ten different structural elements with various shapes (the biggest is $5\times5$).
+for each image, we radomly sample the operator type (dilation or erosion) and one structural element
+from a subset depending of the complexity (the higher the complexity, the biggest the structural element can be).
+Erosion allows only the five smallest structural elements because when the character is too thin it may erase it completly.
+
 \subsection{Affine Transformations}
-\subsection{Adding Slant}
+We generate an affine transform matrix according to the complexity level, then we apply it directly to the image.
+This allows to produce scaling, translation, rotation and shearing variances. We took care that the maximum rotation applied
+to the image is low enough not to confuse classes.
+
 \subsection{Local Elastic Deformations}
-\subsection{Changing Thickness}
+\subsection{GIMP transformation}
 \subsection{Occlusion}
 \subsection{Background Images}
 \subsection{Salt and Pepper Noise}
@@ -140,7 +157,7 @@
 
 \section{Conclusions}
 
-\bibliography{strings,ml,aigaion}
+\bibliography{strings,ml,aigaion,specials}
 \bibliographystyle{mlapa}
 
-\end{document}
\ No newline at end of file
+\end{document}