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Algorithmes, architecture et éléments optiques pour l'acquisition embarquées d'images totalement focalisées et annotées en distance

Abstract : Acquiring the depth of a scene in addition to its image is a desirable feature for many applications which depend on the near environment. The state of the art in the field of depth extraction offers many methods, but very few are well adapted to small embedded systems. Some of them are too cumbersome because of their large optical system. Others might require a delicate calibration or processing methods which are difficult to implement in an embedded system. In this PhD thesis, we focus on methods with low hardware complexity in order to propose algorithms and optical solutions that extract the depth of the scene, provide a relevance evaluation of this measurement and produce all-in-focus images. We show that Depth from Focus (DfF) algorithms are the most adapted to embedded electronics constraints. This method consists in acquiring a cube of multi-focus images of the same scene for different focusing distances. The images are analyzed in order to annotate each zone of the scene with an index relative to its estimated depth. This index is then used to build an all in focus image. We worked on the sharpness criterion in order to propose low complexity solutions, only based on additions and comparisons, easily adaptable on a hardware architecture. The proposed solution uses bidirectional local contrast analysis and then combines the most relevant depth estimations based on detection confidence at the end of treatment. It is declined in three approaches which need less and less processing and thus make them more and more adapted for a final embedded solution. For each method, depth and confidence maps are established, as well as an all-in-focus image composed of elements from the entire multi-focus cube. These approaches are compared in quality and complexity with other state-of-the-art methods which present similar complexity. A hardware implementation of the best solution is proposed. The design of these algorithms raises the problem of image quality. It is indeed essential to have a remarkable contrast evolution as well as a motionless scene during the capture of the multi-focus cube. A very often neglected effect in this type of approach is the parasitic zoom caused by the lens motion during a focus variation. This "focal zoom" weakens the invariance aspect of the scene and causes artifacts on the depth and confidence maps and on the all in focus image. The search for optics adapted to DfF is thus a second line of research in this work. We have evaluated industrial liquid lenses and experimental nematic liquid crystal modal lenses designed during this thesis. These technologies were compared in terms of speed, image quality, generated focal zoom intensity, power supply voltage and finally the quality of extracted depth maps and reconstructed all in focus images. The lens and the algorithm which best suited this embedded DfF issue were then evaluated on a CPU-GPU development platform allowing real time acquisition of depth maps, confidence maps and all in focus images.
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Simon Emberger. Algorithmes, architecture et éléments optiques pour l'acquisition embarquées d'images totalement focalisées et annotées en distance. Micro et nanotechnologies/Microélectronique. Ecole nationale supérieure Mines-Télécom Atlantique, 2017. Français. ⟨NNT : 2017IMTA0055⟩. ⟨tel-01800048⟩

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