arXiv subjects

Hossein Hosseinzadeh

Publications and source records attributed to Hossein Hosseinzadeh.

6 recordsLinked to original sources

arXiv2024

Enhanced Facial Feature Extraction and Recignation Using Optimal Fully Dispersed Haar-like Filters

Haar-like filters are renowned for their simplicity, speed, and accuracy in various computer vision tasks. This paper proposes a novel algorithm to identify optimal fully dispersed Haar-like filters for enhanced facial feature extraction and recognation. Unlike traditional Haar-like filters, these novel filters allow pixels to move freely within images, enabling more effictive capture of intricate local features...

cs.CV↗

arXiv2024

Local Binary Pattern(LBP) Optimization for Feature Extraction

The rapid growth of image data has led to the development of advanced image processing and computer vision techniques, which are crucial in various applications such as image classification, image segmentation, and pattern recognition. Texture is an important feature that has been widely used in many image processing tasks. Therefore, analyzing and understanding texture plays a pivotal role in image analysis and understanding.Local binary pattern (LBP) is a powerful operator that describes the local texture features of images. This paper provides a novel mathematical representation of the LBP by separating the operator into three matrices, two of which are always fixed and do not depend on the input data. These fixed matrices are analyzed in depth, and a new algorithm is proposed to optimize them for improved classification performance. The optimization process is based on the singular value decomposition (SVD) algorithm. As a result, the authors present optimal LBPs that effectively describe the texture of human face images. Several experiment results presented in this paper convincingly verify the efficiency and superiority of the optimized LBPs for face detection and facial expression recognition tasks.

cs.CV↗

arXiv2024

The use of the symmetric finite difference in the local binary pattern (symmetric LBP)

The paper provides a mathematical view to the binary numbers presented in the Local Binary Pattern (LBP) feature extraction process. Symmetric finite difference is often applied in numerical analysis to enhance the accuracy of approximations. Then, the paper investigates utilization of the symmetric finite difference in the LBP formulation for face detection and facial expression recognition. It introduces a novel approach that extends the standard LBP, which typically employs eight directional derivatives, to incorporate only four directional derivatives. This approach is named symmetric LBP. The number of LBP features is reduced to 16 from 256 by the use of the symmetric LBP. The study underscores the significance of the number of directions considered in the new approach. Consequently, the results obtained emphasize the importance of the research topic.

cs.CV↗

arXiv2023

Radial boundary elements method, a new approach on using radial basis functions to solve partial differential equations, efficiently

Conventionally, piecewise polynomials have been used in the boundary elements method (BEM) to approximate unknown boundary values. Since infinitely smooth radial basis functions (RBFs) are more stable and accurate than the polynomials for high dimensional domains, the unknown values are approximated by the RBFs in this paper. Therefore, a new formulation of BEM, called radial BEM, is obtained. To calculate singular boundary integrals of the new method, we propose a new distribution for boundary source points that removes singularity from the integrals. Therefore, the boundary integrals are calculated precisely by the standard Gaussian quadrature rule (GQR) with n = 16 quadrature nodes. Several numerical examples are presented to check the efficiency of the radial BEM versus standard BEM and RBF collocation method for solving partial differential equations (PDEs). Analytical and numerical studies presented in this paper admit the radial BEM as a perfect version of BEM which will enrich the contribution of BEM and RBFs in solving PDEs, impressively.

math.NA↗

arXiv2023

Radial polynomials as alternatives to smooth radial basis functions and their applications

Because of the high approximation power and simplicity of computation of smooth radial basis functions (RBFs), in recent decades they have received much attention for function approximation. These RBFs contain a shape parameter that regulates the relation between their accuracy and stability. A difficulty in approximation via smooth RBFs is optimal selection of shape parameter. The aim of this paper is to introduce an alternative for smooth RBFs, which in addition to overcoming this difficulty, its approximation power is almost equal to RBFs....

math.NA↗

arXiv2017

Janus: An Uncertain Cache Architecture to Cope with Side Channel Attacks

Side channel attacks are a major class of attacks to crypto-systems. Attackers collect and analyze timing behavior, I/O data, or power consumption in these systems to undermine their effectiveness in protecting sensitive information. In this work, we propose a new cache architecture, called Janus, to enable crypto-systems to introduce randomization and uncertainty in their runtime timing behavior and power utilization profile. In the proposed cache architecture, each data block is equipped with an on-off flag to enable/disable the data block. The Janus architecture has two special instructions in its instruction set to support the on-off flag. Beside the analytical evaluation of the proposed cache architecture, we deploy it in an ARM-7 processor core to study its feasibility and practicality. Results show a significant variation in the timing behavior across all the benchmarks. The new secure processor architecture has minimal hardware overhead and significant improvement in protecting against power analysis and timing behavior attacks.

cs.CR↗