Khalid Zenkouar

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Research investigating the use of Legendre moments for pattern recognition has been performed in recent years. This field of research remains quite open. This paper proposes a new technique based on block-based reconstruction method (BBRM) using Legendre moments compared with the global reconstruction method (GRM). For alleviating the blocking artifact(More)
Discrete Tchebichef moments are widely used in the field of image processing application and pattern recognition. In this paper we propose a compact method of 3D Tchebichef moments computation. This new method based on Clenshaw's recurrence formula and the symmetry property produces a drastic reduction in the complexity and computational time. The recursive(More)
Three-Dimensional Hahn moments are performant tool in the domain of image processing applications and pattern classification. In this work, we propose a new method for computing the Three-Dimensional Hahn moments. This method is based on matrix multiplication and symmetry property to decrease the complexity and computational time for volumetric image(More)
Discrete Tchebichef moments are wid ely used in the field of image processing application and pattern recognition. In this paper we propose a compact method of 3D Tchebichef moments computation. This new method based on Clenshaw's recurrence formula and the symmetry property produces a drastic reduction in the complexity and computational time. The(More)
In this paper, we suggest a new technique for fast computation of Gegenbauer orthogonal moments for the reconstruction of 3D images/objects; A typical comparison of the proposed method with the conventional ZOA methods shows significant improvements in term of error reduction and image quality. Then we compare our new approach with an existing method using(More)
In this paper, we propose a novel method for reconstruction of the multi-gray level images using the exact computation of Legendre moments. The purpose of this method is to ensure high accuracy and low computation time, by dividing the image into a set of blocks instead of treating the whole image. For mitigating the blocking artifact involved in the(More)
Prediction of solar radiation plays an important role in different energy systems. The aim of this paper is twofold: firstly, we provide an updated review of solar radiation prediction models using ANN's, based on 32 retained papers, by specifying the prediction horizon, ANN architecture and the corresponding obtained performance indicators. Secondly,(More)