Méthodes robustes pour l'estimation d'illuminants et la prise en compte de la couleur en comparaison d'images

Abstract : This thesis addresses the use of color in image processing and computer vision. Two problems are studied: - illuminant estimation, - local descriptors matching for color images comparison. Achromatic surfaces are defined as surfaces reflecting a spectrum with the same frequency dsitribution than the illuminant. Consequently, revovering these surfaces allows to estimate the illuminant. Assuming that the range of colors taken by an illuminant is limited (Planck equation), it is possible to select the pixels belonging to a potentially gray surface. A voting procedure is then applied to select one or more illuminants. The proposed algorithm has many advantages: it is effective, intuitive, does not rely on a learning phase and requires only few parameters. In addition, the voting procedure can be adapted to handle cases where multiple light sources of different colors illuminate the scene. Local descriptors are powerful tools to compare images. However, few studies concern the influence of color in the matching step. The main problem that we consider here is the contribution of the color matching of local descriptors. Does the local use of color allow to disambiguate situations where the luminance alone is insufficient ? And if so, how much? We propose four descriptors to precisely describe the local context of key points in the matching step. The main idea developed here is that accurate information can only be obtained by describing both the color distributions and transitions between colors. The many experiences presented clearly show the positive contribution of color to the reliability of the local matching.
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Baptiste Mazin. Méthodes robustes pour l'estimation d'illuminants et la prise en compte de la couleur en comparaison d'images. Vision par ordinateur et reconnaissance de formes [cs.CV]. Télécom ParisTech, 2014. Français. ⟨NNT : 2014ENST0016⟩. ⟨tel-01547852⟩

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