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Dive into the research topics where Nabil El Akkad is active.

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Featured researches published by Nabil El Akkad.


The Visual Computer | 2014

Camera self-calibration with varying intrinsic parameters by an unknown three-dimensional scene

Nabil El Akkad; Mostafa Merras; Abderrahim Saaidi; Khalid Satori

This work proposes a method of camera self-calibration having varying intrinsic parameters from a sequence of images of an unknown 3D object. The projection of two points of the 3D scene in the image planes is used with fundamental matrices to determine the projection matrices. The present approach is based on the formulation of a nonlinear cost function from the determination of a relationship between two points of the scene and their projections in the image planes. The resolution of this function enables us to estimate the intrinsic parameters of different cameras. The strong point of the present approach is clearly seen in the minimization of the three constraints of a self-calibration system (a pair of images, 3D scene, any camera): The use of a single pair of images provides fewer equations, which minimizes the execution time of the program, the use of a 3D scene reduces the planarity constraints, and the use of any camera eliminates the constraints of cameras having constant parameters. The experiment results on synthetic and real data are presented to demonstrate the performance of the present approach in terms of accuracy, simplicity, stability, and convergence.


Journal of Visual Communication and Image Representation | 2016

A flexible technique based on fundamental matrix for camera self-calibration with variable intrinsic parameters from two views

Bouchra Boudine; Sebastien Kramm; Nabil El Akkad; Abdelaziz Bensrhair; Abderrahim Saaidi; Khalid Satori

Self-calibrate cameras with varying focal length.Automatic estimation of the intrinsic parameters of the camera.Works freely in the domain of self-calibration without any prior knowledge about the scene or on the cameras. We propose a new self-calibration technique for cameras with varying intrinsic parameters that can be computed using only information contained in the images themselves. The method does not need any a priori knowledge on the orientations of the camera and is based on the use of a 3 D scene containing an unknown isosceles right triangle. The importance of our approach resides at minimizing constraints on the self-calibration system and the use of only two images to estimate these parameters. This method is based on the formulation of a nonlinear cost function from the relationship between two matches which are the projection of two points representing vertices of an isosceles right triangle, and the relationship between the images of the absolute conic. The resolution of this function enables us to estimate the cameras intrinsic parameters. The algorithm is implemented and validated on several sets of synthetic and real image data.


international conference on multimedia computing and systems | 2012

Self-calibration based on a circle of the cameras having the varying intrinsic parameters

Nabil El Akkad; Abderrahim Saaidi; Khalid Satori

The problem examined in this article is a cameras self-calibration having the varying intrinsic parameters with an unknown planar scene. This method is based on the use of two points through which passes a circle. The planar scene considered permits to calculate the projection matrices of any two points of the scene in used images. These matrices can minimize a non-linear cost function to optimize the initial intrinsic parameters.


soft computing | 2018

Multi-view 3D reconstruction and modeling of the unknown 3D scenes using genetic algorithms

Mostafa Merras; Abderrahim Saaidi; Nabil El Akkad; Khalid Satori

This paper presents a complete pipeline of the reconstruction and the modeling of the unknown complex 3D scenes from a sequence of unconstrained images. The proposed system is based on the formulation of a nonlinear cost function by determining the relationship between 2D points of the images and the cameras parameters; the optimization of this function by a genetic algorithm makes finding the optimal cameras parameters. The determination of these parameters allows thereafter to estimate the 3D points of the observed scene. Then, the mesh of the 3D points is achieved by 3D Crust algorithm and the texture mapping is performed by multiple dependent viewpoints. Extensive experiments on synthetic and real data are performed to validate the proposed approach, and the results indicate that our system is robust and can achieve a very satisfactory reconstruction quality.


The Visual Computer | 2018

3D reconstruction system based on incremental structure from motion using a camera with varying parameters

Soulaiman El Hazzat; Mostafa Merras; Nabil El Akkad; Abderrahim Saaidi; Khalid Satori

In this paper, we present a flexible and fast system for multi-scale objects/scenes 3D reconstruction from uncalibrated images/video taken by a moving camera characterized by variable parameters. The proposed system is based on incremental structure from motion and good exploitation of bundle adjustment. At first, from two selected images, our system allows to recover, in a well-chosen reference, coordinates of a set of 3D points. In this context, we have proposed a new method of self-calibration based on the use of two unknown scene points with their image projections. After that, new images are inserted progressively using 3D information already obtained. Local bundle adjustment is used to adjust the new estimated entities. At some time, we introduce a global bundle adjustment to adjust as best as possible all estimated entities and to have an initial 3D model of quality covering an interesting part of the object/scene. This model will be used as reference for the insertion of the rest of images. The proposed system allows to obtain satisfactory results within a reasonable time.


Multimedia Tools and Applications | 2018

Camera self-calibration having the varying parameters and based on homography of the plane at infinity

Nabil El Akkad; Mostafa Merras; Aziz Baataoui; Abderrahim Saaidi; Khalid Satori

In this approach, we will process a self-calibration problem of camera characterized by varying parameters. Our approach is based on estimating of homography of the plane at infinity and depths of interest points. This estimation is made from resolution of nonlinear equation system that is formulated from the projection of some points of the scene in the planes of different images. The relationships established between the homography of the plane at infinity and matches, between images, and those established between points of the 3D scene and their projections, in image planes, allow formulating the second nonlinear equations. This system is minimized by using the Levenberg-Marquardt algorithm to estimate the intrinsic parameters of used camera. This approach has several strong points: i) The use of any cameras (having varying parameters), ii) The use of any scenes (3D) and iii) the use of a minimum number of images (two images only). Experiments and simulations show the performance of this approach in terms of stability, accuracy and convergence.


international conference on big data | 2018

A Novel Text Encryption Algorithm Based on the Two-Square Cipher and Caesar Cipher

Mohammed Es-sabry; Nabil El Akkad; Mostafa Merras; Abderrahim Saaidi; Khalid Satori

Security of information has become a popular subject during the last decades, it is the balanced protection of the Confidentiality, Integrity and Availability of data, also known as the CIA Triad. In this work, we introduce a new hybrid system based on two different encryption techniques: two square cipher and Caesar cipher with multiples keys. This homogeneity between the two systems allows us to provide the good properties of the two square cipher method and the simplicity of the Caesar cipher method. The security analysis shows that the system is secure enough to resist brute-force attack, and statistical attack. Therefore, this robustness is proven and justified.


international conference on big data | 2018

Reconstruction of the 3D Scenes from the Matching Between Image Pair Taken by an Uncalibrated Camera

Karima Karim; Nabil El Akkad; Khalid Satori

In this paper, we will study a new approach of reconstruction of three-dimensional scenes from an auto calibration method of camera characterized by variable parameters. Indeed, obtaining the 3D scene is based on the Euclidean reconstruction of the interest points detected and matched between pair of images. The relationship between the matches and camera parameters is used to formulate a nonlinear equation system. This system is transformed into a nonlinear cost function, which will be minimized to determine the intrinsic and extrinsic camera parameters and subsequently estimate the projection matrices. Finally, the coordinates of the 3D points of the scene are obtained by solving a linear equation system. The results of the experiments show the strengths of this contribution in terms of precision and convergence.


international conference on multimedia computing and systems | 2014

Method of 3D mesh reconstruction from sequences of calibrated images

Mostafa Merras; Nabil El Akkad; Soulaiman El Hazzat; Abderrahim Saaidi; Abderrazak Gadhi Nazih; Khalid Satori

In this paper we propose a technical mesh of an unknown 3D scene from two or more images taken by cameras having the constant parameters based on genetic algorithms. The present approach is based on the formulation of a nonlinear cost function from the determination of a relationship between points of the image planes and all parameters of the cameras. The minimization of this function by a genetic approach enables us to simultaneously estimate the intrinsic and extrinsic parameters of the cameras. These parameters are used with matching to determine the 3D point clouds. The mesh generation is performed by Delaunay triangulation. The strong point of this approach can be clearly seen in the minimization of the constraints of a self-calibration system: The use a genetic algorithm to accelerate the speed of convergence and avoid local minima to obtain a good estimation of the camera parameters and the use of a 3D scene reduces the planarity constraints. Our study is performed on real data to demonstrate the validity and performance of the presented approach in terms of accuracy, simplicity, stability, and convergence.


3d Research | 2015

Camera Self Calibration with Varying Parameters by an Unknown Three Dimensional Scene Using the Improved Genetic Algorithm

Mostafa Merras; Nabil El Akkad; Abderrahim Saaidi; Abderrazak Gadhi Nazih; Khalid Satori

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Khalid Satori

Sidi Mohamed Ben Abdellah University

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Abderrahim Saaidi

Sidi Mohamed Ben Abdellah University

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Mostafa Merras

Sidi Mohamed Ben Abdellah University

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Soulaiman El Hazzat

Sidi Mohamed Ben Abdellah University

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Abderrazak Gadhi Nazih

Sidi Mohamed Ben Abdellah University

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Mohammed Es-sabry

Sidi Mohamed Ben Abdellah University

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Aziz Baataoui

Sidi Mohamed Ben Abdellah University

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Karima Karim

Sidi Mohamed Ben Abdellah University

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