Rabiâ RIAD

• PhD
• Professor (Associate) at University Ibn Zohr - Agadir

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This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. The authors first present a synthesis of the major recent influencing techniques and "tricks" participating in r...

Feature selection plays a crucial role in machine learning by identifying the most relevant and informative features from the input data, leading to improved model performance and reduced computational complexity. Deep learning, with its ability to automatically learn hierarchical representations from data, has shown promise in feature extraction t...

This chapter provides a comprehensive overview of traditional clustering algorithms, which have been fundamental in the field of unsupervised learning. The strengths and limitations of each algorithm are carefully examined, along with guidelines for selecting the most appropriate method based on the dataset characteristics and clustering objectives...

This chapter serves as a comprehensive guide to deep clustering techniques, offering a deeper understanding of their underlying principles, architectures, applications, and evaluation methodologies. It is a valuable starting resource for researchers, practitioners, and students interested in exploring the synergies between deep learning and cluster...

This chapter presents the most popular deep clustering techniques based on Autoencoder architectures. From pioneering approaches such as Deep Embedding Network for Clustering (DEN) or Deep Embedded Clustering (DEN) to more contemporary methods such as Not to Deep (N2D), we not only aim to present these methods but also provide insights into the inv...

Clustering validation and identifying the optimal number of clusters are crucial in expert and intelligent systems. However, the commonly used cluster validity indices (CVI) are not relevant enough to measure data structures. They do not embed the necessary mechanisms to be as effective as that of the clustering algorithm used to give the clusterin...

Currently, most transactions and exchanges are conducted through the Internet thanks to technological tools, running the risk of the falsification and distortion of information. This is due to the massive demand for the virtual world and its easy access to anyone. Image watermarking has recently emerged as one of the most important areas for protec...

A new clustering algorithm Path-scan aiming at discovering natural partitions is proposed. It is based on the idea that a (k,ɛ) coreset of the original data base represented by core and support patterns can be path-connected via a density differential approach. The Path-scan algorithm is structured in two main parts producing a connectivity matrix...

Background removal of an identity (ID) picture consists in separating the foreground (face, body, hair and clothes) from the background of the image. It is a necessary groundwork for all modern identity documents that also has many benefits for improving ID security. State of the art image processing techniques encountered several segmentation issu...

Watermarking for identity images printed on a plastic card support is still challenging. In this application, the scheme must be robust against a combination of geometric and signal processing attacks related to the print/scan process. In addition, the scheme must deal with all the possible aggressions that a smart card can encounter during its lif...

Density-based clustering algorithms have made a large impact on a wide range of application fields application. As more data are available with rising size and various internal organizations, non-parametric unsupervised procedures are becoming ever more important in understanding datasets. In this paper a new clustering algorithm S-DBSCAN¹ is propo...

Digital image watermarking is an active research field since it provides protection, security, and authenticity of data. This paper presents development and implementation of a blind and robust watermarking application for ID images under a print-cam system. In the present case, the images are watermarked and printed on ID cards and then detected f...

OsteoArthritis (OA) is a joint disease caused by cartilage loss in the joint and bone changes. Early knee OA prediction based on bone texture analysis is a difficult task in medical image analysis. This paper presents a new approach based on concepts of complex network theory to extract texture features related to OA from radiographic knee X-ray im...

Geometric attacks are still challenging issues in image watermarking. In this paper, the robustness of different insertion position and shape of the watermark are evaluated in watermarking scheme based on Fourier-Mellin transform. We propose diagonal, rectangular, and circular insertion of the mark. The robustness of these techniques against geomet...

New clustering algorithms are expected to manage complex data, meaning various shapes and densities while being user friendly. This work addresses this challenge. A new clustering algorithm KdMutual ¹ driven by the number of clusters is proposed. The idea behind the algorithm is based on the assumption that working with cluster cores rather than co...

Trabecular bone (TB) characterization for osteoporosis diagnosis on plain radiographic images presents a challenging task in medical imaging. The goal of this paper is to study the information of complex wavelet coefficients to extract descriptors of the trabecular bone. These descriptors are extracted using some statistics of a new relative phase...

In this paper, an aided diagnosis method for OsteoArthritis (OA) disease using knee X-ray imaging and spectral analysis is presented. The proposed method is based on the Power Spectral Density (PSD) over different orientations of the image as a feature for the classification task. Then, independent component analysis (ICA) is used to select the rel...

This paper presents a fully developed computer aided diagnosis (CAD) system for early knee OsteoArthritis (OA) detection using knee X-ray imaging and machine learning algorithms. The X-ray images are first preprocessed in the Fourier domain using a circular Fourier filter. Then, a novel normalization method based on predictive modeling using multiv...

Smartphone watermarking has many potential applications but also many challenging issues such as being able to withstand print-cam attacks. These include perspective deformations that can strongly deform the freehandedly digitized image. In this paper, we present the design of an image watermarking for print-cam process in the context of an industr...

Abstract The classification of subjects with different stages of knee OsteoArthritis (OA) using bone texture analysis is a challenging task in medical imaging. This paper presents a new approach for texture analysis of radiographic OA in knee X-ray images. First, a preprocessing step based on a 2D finite impulse response filter is applied on the X-...

Fourier watermarking is often chosen to watermark images that have to be printed and scanned on a physical support, during which the so-called print-scan attack occurs. One popular method embeds the watermark in the FFT magnitudes of the image along a circle of optimal radius. This paper presents an enhancement of Fourier watermarking robustness by...

Security checking can be improved by watermarking identity (ID) images printed on smart cards plastic supports. The major challenge is resistance to attacks: printing the images on the plastic cards, durability and other attacks then scanning the image from the plastic card. In this work, a robust watermarking technique is presented in this context...

Modeling the human visual system has become an important issue in image processing such as compression, evaluation of image quality and digital watermarking. In this paper we present a spatial JND (Just Noticeable-Difference-) model that uses a texture selector based on Faber-Schauder wavelets lifting scheme. This texture selector identify non-unif...

Perspective deformation is one of the major issues in print-cam attacks for image watermarking. In this paper we adapt to print-cam process a Fourier watermarking method developed by our team, for print-scan attacks. Our aim is to resist to perspective distortions of print-cam image watermarking for ID images for industrial application. A first ste...

Invisible watermarking for ID images printed on plastic card support is a challenging problem that interests the industrial world. In this thesis, we developed a robust watermarking algorithm that resists to various attacks occur in the ID card field. These attacks are mainly related to the print/scan process and the lifetime degradations of ID car...

The print-scan operation is still challenging in the watermarking community, some watermarking techniques were proposed in the literature to deal with this operation. These watermarking techniques are still very sensitive to degradations produced by the print-scan process. This paper investigates a watermarking technique in the Fourier domain that...

In recent years an interest has emerged in the fields of meteoritic sciences such as X-ray Computed Tomography (CT), which is a nondestructive method that produces three-dimensional (3D) images of the internal features of rock specimens. To analyze the characteristics of meteorites, it is critical that the elements constituting can be distinguished...

Watermark robustness against both geometric and signal processing attacks is still challenging in the watermarking community. In this work, we propose an approach to increase the watermark detection rate. The novel feature of the method resides in pre-processing the image before the embedding process, and involves no interaction with other improvem...

In the context of an industrial application for securing identity cards, image watermarking is used to verify the integrity and authenticity of images printed on plastic cards support. In this area the watermark must survive image modifications related to print-and-scan process and the degradations submitted by ID cards through its lifetime. In thi...

In recent past years, Fourier based watermarking techniques have been developed to deal with the print-and-scan attack. In this work, print-and-scan counterattacks for Fourier watermarking are proposed in the context of an industrial application where identity (ID) images are printed and scanned on a plastic card support. The counterattacks are wit...