Président du jury Legros, Jean Claude
Promoteur Dubois, Frank
Publication Non publié, 2007-02-26
| Résumé : | Digital Holography Microscopy (DHM) is a new 3D measurement technique that exists since Charge Coupled Devices (or CCD cameras) allow to record numerically high resolution images. That opens a new door to the theory of holography discovered in 1949 by Gabor: the door that masked the world of digital hologram processing. A hologram is a usual image but that contains the complex amplitude of the light coded into intensities recorded by the camera. The complex amplitude of the light can be seen as the combination of the energy information (squared amplitude modulus) with the information of the propagation angle of the light (phase of the amplitude) for each point of the image. When the hologram is digital, this dual information associated with a diffractive model of the light propagation permits to numerically investigate back and front planes to the recorded plane of the imaging system. We understand that 3D information can be recorded by a CCD camera and the acquisition rate of this volume information is only limited by the acquisition rate of the unique camera. For each digital hologram, the numerical investigation of front and back regions to the recorded plane is a tool to numerically refocus objects appearing unfocused in the original plane acquired by the CCD. This thesis aims to develop general and robust algorithms that are devoted to automate the analysis process in the 3D space and in time of objects present in a volume studied by a specific imaging system that permits to record holograms. Indeed, the manual processing of a huge amount of holograms is not realistic and has to be automated by software implementing precise algorithms. In this thesis, the imaging system that records holograms is a Mach-Zehnder interferometer working in transmission and studied objects are either of biological nature (crystals, vesicles, cancer cells) or latex particles. We propose and test focus criteria, based on an identical focus metric, for both amplitude and phase objects. These criteria allow the determination of the best focus plane of an object when the numerical investigation is performed. The precision of the best focus plane is lower than the depth of field of the microscope. From this refocus theory, we develop object detection algorithms that build a synthetic image where objects are bright on a dark background. This detection map of objects is the first step to a fully automatic analysis of objects present in one hologram. The combination of the detection algorithm and the focus criteria allow the precise measurement of the 3D position of the objects, and of other relevant characteristics like the object surface in its focus plane, or its convexity or whatever. These extra relevant measures are carried out with a segmentation algorithm adapted to the studied objects of this thesis (opaque objects, and transparent objects in a uniform refractive index environment). The last algorithm investigated in this research work is the data association in time of objects from hologram to hologram in order to extract 3D trajectories by using the predictive Kalman filtering theory. These algorithms are the abstract bricks of two software: DHM Object Detection and Analysis software, and Kalman Tracking software. The first software is designed for both opaque and transparent objects. The term object is not defined by one other characteristic in this work, and as a consequence, the developed algorithms are very general and can be applied on various objects studied in transmission by DHM. The tracking software is adapted to the dynamic applications of the thesis, which are flows of objects. Performance and results are exposed in a specific chapter. |
