المؤتمـــــــرات

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Browsing المؤتمـــــــرات by Author "Bekkouche, Tewfik"

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    Biometric Image Encryption Scheme based on Modified Double Random Phase Encoding System
    (University of Oum El Bouaghi, 2021-05-25) Yahi, Amina; Bekkouche, Tewfik; Diffellah, Nacira; Daachi, Mohamed El Hossine
    In this paper, an opto-digital encryption scheme based on a modified Double Random Phase Encoding (DRPE) system is proposed. Two biometric modalities are used in this work which is the face and the corresponding finger print of the same person. Firstly the face biometric image is encrypted chaotically using the permutation-diffusion architecture. Then obtained encrypted face is multiplied element by element by a constructed mask formed by injecting the finger print image within the phase of this mask. The obtained result will be transformed into a frequency domain by the two-dimensional. Fourier transform or any of its derivatives, resulting complex image is exactly the encrypted biometric image. Experiment computer simulations confirm the efficiency of this work in terms of histogram analysis, loss data and sensitivity test when compared with existing works.
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    Image denoising algorithms using norm minimization techniques
    (University of Oum El Bouaghi, 2021-05-25) Diffellah, Nacira; Bekkouche, Tewfik; Hamdini, Rabah
    Image denoising is one of the fundamental image processing problems. Noise removal is an important step in the image restoration process. In this paper, firstly we develop and implement two different image denoising algorithms based on norm minimization, namely `1 and `2-regularization applied to images contaminated by gaussian noise. Then, after their discretization and implementation, we perform a comparison between the two methods using several test images. Through this study, the algorithm which minimizes `2-norm of gradient of image has a unique solution and it’s easy to implement, but it doesn’t accept contour discontinuities, causing the obtained solution to be smooth. The `2-norm will blur the edges of the image. In order to preserve sharp edges, `1-norm is introduced. There are different methods to solve the problem of energy minimization. In this work, we have chosen the discretization finite difference method before applying the gradient descent algorithm to optimize the signal (2D grayscale images) denoising functionality. Experiments results, show that `1 regularization encourages image smoothness while allowing for presence of jumps and discontinuities, a key feature for image processing because of the importance of edges in human vision.