\chapter{Introduction}
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In this thesis, we propose an automatic  visual recognition system for biological particles. 
In particular, we focus on recognition of particles that are
found in microscopic urinalysis, and we also deal with the recognition of airborne pollen grains. \\
Our approach is general, segmentation free, able to achieve a very good performance on many different categories of particles. For these reasons, the system is suitable to be used for recognition of other kinds of biological particles.\\

In chapter \ref{sec:microana}, we describe the goal of microscopic analysis in aerobiology and in urinalysis and the usually
applied techniques. We conclude this part with an assessment on the need to automate these analyses that will justify this research.\\
Chapter \ref{sec:database} introduces our databases giving a complete list of available images with a brief description about their
characteristics.\\ 
The following chapter provides an overview on related work which is 
a reference point to evaluate the performance of our system. Moreover, we introduce the main stages of a recognition system: detection and
classification.\\
Chapter \ref{sec:detector} tackles the problem of particle detection in a given image. 
We will discuss two approaches having different performances and advantages. The first detector is based on a filtering technique while the
second one on morphological operations. \\
Chapter \ref{sec:feature} reviews the features developed for the classifier. These features are derived from previous work of Schmid et al.
\cite{paper:Schmid} and Torralba et al. \cite{paper:ipcspc}. Thanks to some kind of elaboration, we are able to get 
from each image a new kind of very informative feature.\\
In chapter \ref{sec:classification}, we discuss many classifiers: Bayesian classifiers, 
a classifier inspired by AdaBoost algorithm and a last one using support vector machines. This chapter is completed by an experimental part
which shows the experiments done to tune the system and to compute the global performance.\\
The following chapter provides an insight about errors done by detector and classifier during the previous experiments.\\
In chapter \ref{sec:ws}, we conclude with an extensive analysis of the performance of a complete system, namely detector followed 
by classifier, for pollen recognition. \\
The last chapter summarizes the main points of this research. We discuss our contribution in automatic visual recognition of particles and the
tasks that will challenge future works.\\

   
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