Évaluation du contenu d'une image couleur par mesure basée pixel et classification par la théorie des fonctions de croyance

Abstract : Nowadays it has become increasingly simpler for anyone to take pictures with digital cameras, to download these images to the computer and to use different image processing software to apply modi- fications on these images (Compression, denoising, transmission, etc.). However, these treatments lead to degradations which affect the visual quality of the image. For this purpose, it is necessary to have effective tools able to measure the impact of these distortions on the image quality. Moreover, in recent years a particular disruption has appeared, namely the embedding of "invisible" messages for legitimate or malicious purposes for confidential or secret communications. Nowadays, with the widespread use of the internet, steganography is becoming a popular practice and easily accessible to anyone who wants to hide a message or communicate in a secret way. Therefore, the need to detect steganographic objects give rise to steganalysis, the dual process of steganography. In this manuscript we discussed two issues : the image quality assessment and the detection of modifi- cation or the presence of hidden information in an image. The first objective is to develop a No-Reference measure allowing to automatically evaluate the quality of an image in correlation with the human visual appreciation. Then we propose a steganalysis scheme to detect, with the best possible reliability, the pre- sence of information embedded in natural images. In this thesis, the challenge is to take into account the imperfection of the manipulated data coming from different sources of information with different degrees of precision. In this context, in order to take full advantage of all this information, we propose to use the theory of belief functions. This theory makes it possible to represent knowledge in a relatively natural way in the form of a belief structure. We proposed a No-reference image quality assessment measure, which is able to estimate the quality of the degraded images with multiple types of distortion. This approach, called wms-EVreg2, is based on the fusion of different statistical features, extracted from the image, depending on the reliability of each set of features estimated through the confusion matrix. From the various experiments, we found that wms- EVreg2 has a good correlation with subjective quality scores and provides competitive quality prediction performance compared to Full-reference image quality measures. For the second problem addressed, we proposed a steganalysis scheme based on the theory of belief functions constructed on random subspaces of the features. The performance of the proposed method was evaluated on different steganography algorithms in the JPEG transform domain as well as in the spatial domain. These experimental tests have shown the performance of the proposed method in some application frameworks. However, there are many configurations that reside undetectable. Keywords : quality assessment, steganography, steganalysis, belief function.
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Submitted on : Friday, January 3, 2020 - 10:26:03 AM
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Nadjib Guettari. Évaluation du contenu d'une image couleur par mesure basée pixel et classification par la théorie des fonctions de croyance. Sciences de l'ingénieur [physics]. Université de poitiers, 2017. Français. ⟨tel-02427016⟩



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