The main objective of this thesis is the development of new processing techniques for digital holograms. The present work is part of the HoloFlow project that intends to integrate the DHM technology for the monitoring of water quality. Different tools for an automated analysis of digital holograms have been developed to detect, refocus and classify particles in continuous fluid flows. A detailed study of the refocusing criterion permits to determine its dependencies and to quantify its robustness. An automated detection procedure has been developed to determine automatically the 3D positions of organisms flowing in the experiment volume. Two detection techniques are proposed: a usual method based on a global threshold and a new robust and generic method based on propagation matrices, allowing to considerably increase the amount of detected organisms (up to 95 %) and the reliability of the detection. To handle the case of aggregates of particles commonly encountered when working with large concentrations, a new separation procedure, based on a complete analysis of the evolution of the focus planes, has been proposed. This method allows the separation aggregates up to an overlapping area of around 80 %. These processing tools have been used to classify organisms where the use of the full interferometric information of species enables high classifier performances to be reached (higher than 93 %). / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished