Papers by Mohammed El Hassouni
Journal of Convergence Information Technology, 2012
This paper deals with the joint modeling of color textures in the context of Content Based Image ... more This paper deals with the joint modeling of color textures in the context of Content Based Image Retrieval (CBIR). We propose a generic multivariate model based on the Generalized Gamma distribution to describe the marginal behavior of texture wavelet detail subbands. Then the information of dependence across color components is incorporated in the modeling process using the Gaussian copula. The multivariate Generalized Gamma distribution (D MG) is advantageous in term of flexibility when compared with other joint models. As similarity measure, we propose a closed-form of the Kullback-leibler (KL) divergence between two Ds MG. Performances of the CBIR system show the superiority of the proposed model over a variety of multivariate models.
Multimedia Tools and Applications
Nowadays, many modalities such as CT, X-ray scanners, MRI/fMRI, PET scan, etc. generate complex i... more Nowadays, many modalities such as CT, X-ray scanners, MRI/fMRI, PET scan, etc. generate complex images with a large amount of data that are becoming extremely difficult to handle. This growing mass of data requires new strategies for the diagnosis of diseases and new therapies. In recent years, particular attention has been paid to computational intelligence methods in multimodal biomedical imaging applications. Inspired by artificial intelligence, mathematics, biology and other fields, these methods can find relationships between different categories of this complex data and provide a set of tools for the diagnosis and monitoring of the disease. This special issue provides a forum to publish original research papers covering the state-ofthe-art, new algorithms, methodologies, theories and implementations of computational intelligence methods for computer-aided diagnostic systems and multimodal biomedical imaging applications such as classification, restoration and registration.
Abstract In wireless sensor network, the power supply is, generally, a non-renewable battery. Con... more Abstract In wireless sensor network, the power supply is, generally, a non-renewable battery. Consequently, energy effectiveness is a crucial factor. To maximize the battery life and therefore, the duration of network service, a robust wireless communication protocol providing a best energy efficiency is required. In this paper, we present a uniform balancing energy routing protocol. In this later the transmission path is chosen for maximizing the whole network lifetime.
Abstract In this paper, we propose a novel approach to model the human skin color. The underlying... more Abstract In this paper, we propose a novel approach to model the human skin color. The underlying approach involves affecting a block's average value at each pixel location, using its surrounding points. The generated skin data are found to follow a generalized Gaussian distribution (GGD) and a mixture of GGDs in the H and S color component, respectively. Next, the model parameters are estimated using the maximum-likelihood (ML) criterion applied to a set of training skin samples.
Abstract Next generation wireless personal area networks (WPAN) are intended for a variety of app... more Abstract Next generation wireless personal area networks (WPAN) are intended for a variety of applications. The multiband OFDM alliance (MBOA) is currently developing a new physical layer (PHY) and medium access control (MAC) protocol, which fit the needs of this mass market. The MBOA standards provide wireless technology offering data rates of up to 480 Mbit/s [1].
Abstract In this paper we propose an efficient local appearance feature extraction method for iri... more Abstract In this paper we propose an efficient local appearance feature extraction method for iris recognition based on steerable pyramid (SP) to captures the intrinsic geometrical structures of iris image. It decomposes the iris image into a set of directional sub-bands with texture details captured in different orientations at various scales, local information is extracted from SP sub-bands using block-based statistics to reduce the required amount of data to be stored.
Abstract In this paper, we make a first attempt to combine face and iris biometrics using an effi... more Abstract In this paper, we make a first attempt to combine face and iris biometrics using an efficient local appearance feature extraction method based on steerable pyramid (SP), to captures the intrinsic geometrical structures of face and iris image, it decomposes the face and iris image into a set of directional sub-bands with texture details captured in different orientations at various scales. Local information is extracted from SP sub-bands using block-based statistics to reduce the required amount of data to be stored.
Abstract Most existing face recognition approaches have limited performance in uncontrolled envir... more Abstract Most existing face recognition approaches have limited performance in uncontrolled environments. Effective face recognition requires several different kinds of feature sets to be taken into account which can integrate heterogeneous and complementary information of the input face images. This paper proposes to fuse two discriminative and complementary feature sets.
Multimodal biometric systems consolidate or fuse information from multiple biometric sources. The... more Multimodal biometric systems consolidate or fuse information from multiple biometric sources. They have been developed to overcome several limitations of each individual biometric system, such as sensitivity to noise, intra class invariability, data quality, non-universality and other factors. In this paper, we propose a general framework of multibiometric identification system based on fusion at matching score level using fuzzy set theory.
In Wireless Sensor Network (WSN), the power supply is generally a non-renewable battery, conseque... more In Wireless Sensor Network (WSN), the power supply is generally a non-renewable battery, consequently, energy effectiveness is a crucial factor. To maximise the battery life and therefore the duration of network service, a robust wireless communication protocol providing a best energy efficiency is required. In this paper, we present an Enhanced Low Energy Clustering Protocol for Routing in WSN (ELECP).
Abstract In this paper, we present a novel approach for face recognition combining classifiers ba... more Abstract In this paper, we present a novel approach for face recognition combining classifiers based on both micro texture in spatial domain provided by local binary pattern (LBP) and macro information in frequency domain acquired from the discrete cosine transform (DCT) to represent facial image. The classification of these two feature sets is performed by using support vector machines (SVMs), which had been shown to be superior to traditional pattern classifiers.
La sécurité des personnes, des biens ou des informations est l'une des préoccupations majeures de... more La sécurité des personnes, des biens ou des informations est l'une des préoccupations majeures de nos sociétés actuelles. La reconnaissance faciale est une des solutions la plus communément employée pour effectuer une identification automatique des personnes.
ABSTRACT. Most existing face recognition approaches have limited performance in uncontrolled envi... more ABSTRACT. Most existing face recognition approaches have limited performance in uncontrolled environments. Effective face recognition requires several different kinds of feature sets to be taken into account which can integrate heterogeneous and complementary information of the input face images. In this paper, we propose to fuse two commonly used face recognition algorithms based on Discrete Cosine Transform (DCT) and Local Binary Patterns (LBP) feature extraction.
… 2009. AICCSA 2009 …, Jan 1, 2009
Abstract In this paper, we propose a novel feature extraction scheme based on the multi-resolutio... more Abstract In this paper, we propose a novel feature extraction scheme based on the multi-resolution curvelet transform for face recognition. The obtained curvelet coefficients act as the feature set for classification, and are used to train the ensemble-based discriminant learning approach, capable of taking advantage of both the boosting and LDA (BLDA) techniques. The proposed method CV-BLDA has been extensively assessed using different databases: the ATT, YALE and FERET, Tests indicate that using curvelet-based features ...
International …, Jan 1, 2009
In this paper, an efficient local appearance feature extraction method based the multi-resolution... more In this paper, an efficient local appearance feature extraction method based the multi-resolution Curvelet transform is proposed in order to further enhance the performance of the well known Linear Discriminant Analysis(LDA) method when applied to face recognition. Each face is described by a subset of band filtered images containing block-based Curvelet coefficients. These coefficients characterize the face texture and a set of simple statistical measures allows us to form compact and meaningful feature vectors. The proposed method is compared with some related feature extraction methods such as Principal component analysis (PCA), as well as Linear Discriminant Analysis LDA, and independent component Analysis (ICA). Two different muti-resolution transforms, Wavelet (DWT) and Contourlet, were also compared against the Block Based Curvelet-LDA algorithm. Experimental results on ORL, YALE and FERET face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.
… and Systems, 2009. …, Jan 1, 2009
Abstract In this paper, an efficient local appearance feature extraction method based the multi-r... more Abstract In this paper, an efficient local appearance feature extraction method based the multi-resolution Curvelet transform is proposed for face recognition. Each face is described by a subset of band filtered images containing block-based Curvelet coefficients. These coefficients characterize the face texture and a set of simple statistical measures allows us to form compact and meaningful feature vectors. The proposed method is compared with some related feature extraction methods such as Principal component analysis (PCA), as well ...
Image Processing, 2003. ICIP 2003. …, Jan 1, 2003
Abstract In this paper, a new multichannel spatio-temporal filter is described for color video se... more Abstract In this paper, a new multichannel spatio-temporal filter is described for color video sequences restoration with the presence of non-Gaussian zero-mean additive noise. To address this problem, we propose a multichannel L-filter optimized by the least mean Kurtosis (LMK) algorithm. Prior to filtering, motion compensation is performed by a robust simultaneous estimation for all color components using an affine linear model. Then, we apply the proposed filter to the reconstructed frames. Experiments were performed on real ...
… (ICIP), Jan 1, 2009
In this paper, an efficient local appearance feature extraction method based steerable pyramid (S... more In this paper, an efficient local appearance feature extraction method based steerable pyramid (S-P) is proposed for face recognition. Local information is extracted from S-P sub-bands using block-based statistics. The underlying statistics allow us to reduce the required amount of data to be stored. The obtained local features are combined at the feature and decision level to enhance face recognition performance. Experimental results on ORL, Yale and FERET face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.
Uploads
Papers by Mohammed El Hassouni