Multispectral imaging and its use for face recognition : sensory data enhancement

Abstract : In this thesis, we focus on multispectral image for face recognition. With such application,the quality of the image is an important factor that affects the accuracy of therecognition. However, the sensory data are in general corrupted by noise. Thus, wepropose several denoising algorithms that are able to ensure a good tradeoff betweennoise removal and details preservation. Furthermore, characterizing regions and detailsof the face can improve recognition. We focus also in this thesis on multispectral imagesegmentation particularly clustering techniques and cluster analysis. The effectiveness ofthe proposed algorithms is illustrated by comparing them with state-of-the-art methodsusing both simulated and real multispectral data sets.
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Ahmed Ben Said. Multispectral imaging and its use for face recognition : sensory data enhancement. Image Processing [eess.IV]. Université de Bourgogne, 2015. English. ⟨NNT : 2015DIJOS008⟩. ⟨tel-01203348⟩

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