\chapter{Database}	\label{sec:database}
\thispagestyle{empty}

This chapter describes the databases we used in our work.
  
A company in biomedical analysis, IRIS, provided us the database of cells in urine; these particles are: red blood cells, white blood cells,
bacteria, hyaline casts, pathological casts, crystals, squamous epithelial cells, non squamous epithelial cells, yeasts, white blood cell
clumps, sperm and mucus. These are twelve categories, samples of this database can be found in \figref{esempioDBUrine3}. The resolution is variable
and goes from 36x36 up to 250x250 pixels with 0.68$\mu m / pix$. \\
\tabref{urineDB} shows the number of images in each class of urine database.\\

\begin{figure}[tbp]
\centering
\includegraphics[width=1\textwidth, height=0.6\textwidth]{./figure/esempioDBUrine3.eps}
\caption{Urine database: samples belonging to the twelve categories.}
\label{figure:esempioDBUrine3}
\end{figure}


\begin{table}[htbp]
\begin{center}
\begin{tabular}{||p{5cm}|{c}||}
\hline
\scshape{class} & \scshape{nr. of samples}\\
\hline 
\hline
\bfseries1. bacteria & 1000 \\
\hline
\bfseries2. w. blood c. clumps & 1000 \\
\hline
\bfseries3. yeast & 1000 \\
\hline
\bfseries4. crystal & 1000 \\
\hline
\bfseries5. hyal casts & 1000 \\
\hline
\bfseries6. path. casts & 860 \\
\hline
\bfseries7. non squam. epith. c. & 999 \\
\hline
\bfseries8. red blood c. & 1000 \\
\hline
\bfseries9. sperm & 1000 \\
\hline
\bfseries10. squam. epith. c. & 1000 \\
\hline
\bfseries11. white blood c. & 1000 \\
\hline
\bfseries12. mucus & 546 \\
\hline
\hline
\end{tabular}
\end{center}
\caption{Number of images in each category of urine database}
\label{tab:urineDB}
\end{table}
   

The other database is a collection of pictures of airborne pollen particles taken with the volumetric spore trap
 (see par. \ref{sec:airbonepollana}) and pictures of pollen grains
collected manually from flowers, so called ``pure'' pollen particles. Two example of these pictures are given in \figref{esempioDBPoll2tipi}.
These images have a resolution of 1024x1280 pixels with 0.5$\mu m / pix$.

\begin{figure}[htbp]
\centering
\includegraphics[width=1\textwidth,height=0.45\textwidth]{./figure/esempioDBPoll2tipi.eps}
\caption{Left side: picture of tape containing particles that are present in the Pasadena air. Right side: picture of ``pure''
pollen particles.}
\label{figure:esempioDBPoll2tipi}
\end{figure}

In order to build this database, we started developing a software for enabling human operators to manually collect
 a large training set, consisting of about 1000 samples of grains of pollen for each of 32 species which are found in Pasadena's area.
For this purpose we built a Matlab graphical user interface (see \figref{labelGUI2}) with which we have already collected up a number 
of samples summarized in \tabref{pollenDB}.
Thanks to this software, we have a reference list which stores for each image the position and the genus of each pollen identified by some
expert. Given this information, we derived two databases of patches centered on pollen particles: the first one collects airborne pollen
grains (see \figref{exampleAirPollen22classesbis}), 
the second one ``pure'' pollen grains. Our database has images with ``pure'' pollen particles because of their easier and faster labeling and because in
this way it is simpler to retrieve a large number of samples which are useful to run pilot experiments (see par. \ref{sec:classFinExp}). 

\newpage

\begin{figure}[tbp]
\centering
\includegraphics[width=0.9\textwidth,height=0.5\textwidth]{./figure/labelGUI.eps}
\caption{Screen shot of software for labeling pollen grains. The expert has to identify pollen particles in the image and to select around them boxes. The color of the box is related to the pollen genus. The user can remove and  zoom boxes, view the previous work and change the confidence of his classification. The output is a list with position and genus of each identified pollen.}
\label{figure:labelGUI2}
\end{figure}

\begin{figure}[tbp]
\centering
\includegraphics[width=0.9\textwidth, height=0.5\textwidth]{./figure/exampleAirPollen22classes.eps}
\caption{Examples of pollen grains collected in Caltech campus. In the last row, there are other particles that are similar to pollen grains and that are found in the acquired images. The average resolution is about 50x50 pixels.}
\label{figure:exampleAirPollen22classesbis}
\end{figure}


\begin{table}[htbp]
\begin{center}
\begin{tabular}{||p{3cm}||*{2}{c|}|}
\hline
\scshape{class}	& \scshape{``pure''} 	& \scshape{air sampler machine}	\\
\hline
\hline
\bfseries ash & 1282 & 75\\
\hline
\bfseries chin. elm & 1916 & 124 \\
\hline
\bfseries oak & 1479 & 66 \\
\hline
\bfseries pecan & 1212 & 5 \\
\hline
\bfseries plantain & 1549 & 0 \\
\hline
\bfseries rumex & 1014 & 0 \\
\hline
\bfseries birch & 342 & 0 \\
\hline
\bfseries cypress & 188 & 37 \\
\hline
\bfseries eucalyp. & 280 & 2 \\
\hline
\bfseries grass & 285 & 2 \\
\hline
\bfseries olive & 309 & 11 \\
\hline
\bfseries pistac. & 314 & 0 \\
\hline
\bfseries walnut & 235 & 18 \\
\hline
\bfseries pine & 99 & 43 \\
\hline
\bfseries liq. amber & 113 & 21 \\
\hline
\bfseries alder & 78 & 13 \\
\hline
\bfseries asteraceae & 0 & 6 \\
\hline
\bfseries c. myrtle & 127 & 2 \\
\hline
\bfseries chenopod & 0 & 20 \\
\hline
\bfseries ginkgo & 0 & 3 \\
\hline
\bfseries mulberry & 0 & 38 \\
\hline
\bfseries palm & 0 & 18 \\
\hline
\bfseries plane t. & 0 & 10 \\
\hline
\bfseries poplar & 0 & 5\\
\hline
\bfseries sycamore & 0 & 16 \\
\hline
\bfseries umbellif. & 0 & 4 \\
\hline
\bfseries unknown & 49 & 23 \\
\hline
\hline
\bfseries \emph{total} & \emph{10871} &  \emph{562} \\
\hline
\hline
\end{tabular}
\end{center}
\caption{Pollen database: patches (pollen grains) extracted from 299 sticky tape images and 778 images having only ``pure'' pollen grains.}
\label{tab:pollenDB}
\end{table}

\clearemptydoublepage
