Prise en compte métrologique de la couleur dans un contexte de classification et d'indexation

Abstract : The PhD thesis objective is to study a colour’s correct and complete processing, respecting metrological constraint. The lack of compatible approaches justified that we reformulate the main image processing tools that are gradient, key point detector and descriptor. The proposed approaches are generic: channel count independent and taking the sensor’s or eye’s sensitivity curves into account.The full-vector gradient is born from this metrological objective. Proof of concept was realised on colour, multi and hyper-spectral images. The extension developed for human vision deficiency opens interesting perspectives to study of the human vision system. This gradient is the centre of the key point detector proposition, also generic.We also showed how necessary was a mathematically valid choice of distance between features. We revealed the importance of the pair feature/distance and completed the work with a pair: RC2O/Kulback-Leibler divergence based on colour differences.For each development, we propose unbiased validation protocols linked to synthetic images generators exploring the most spatial-chromatic complexity possible. Our hypothesis being that the extraction difficulty comes from the discrimination complexity between colour distributions in the processing area. We also compared our proposition to state of the art approaches in recurring datasets/protocols.
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Hermine Chatoux. Prise en compte métrologique de la couleur dans un contexte de classification et d'indexation. Traitement du signal et de l'image [eess.SP]. Université de Poitiers, 2019. Français. ⟨NNT : 2019POIT2267⟩. ⟨tel-02179676⟩

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