Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition

Boltzmann mach ine neural network bas been used to recognize the Arabic speech.  Fast Fourier transl(>lmation algorithm has been used t() extract speciral 'features from an a caustic signal .

The  spectral  feature size is reduced by series of operations in

order to make it salable as input for a neural network which is used as a recogni zer by Boltzmann Machine Neural  network which has been used as a recognizer for phonemes . A training set consist of a number of Arabic phoneme repesentations, is used to train lhe neuntl network.

The neural network recognized Arabic. After Boltzmann Machine Neura l    network   training  the  system   with 

  In the present paper, Arabic Character Recognition  Edge detection method based on contour and connected components  is proposed. First stage contour extraction feature is introduced to tackle the Arabic characters edge detection problem, where the aim is to extract the edge information presented in the Arabic characters, since it is crucial to understand the character content.         The second stage connected components appling for the same characters to find edge detection. The proposed approach exploits a number of connected components, which move on the character by character intensity values, to establish matrix, which represents the edge information at each pixel location .

In the present work, steady two – dimensional laminar natural convection heat transfer of Newtonian and non-Newtonian fluids inside isosceles triangular enclosure has been analyzed numerically for a wide range of the modified Rayleigh numbers of (10³ ≤ Ra ≤ 10⁵), with non-dimensional parameter (NE) of Prandtl – Eyring model ranging from (0 to 10), and modified Prandtl number take in the range (Pr* =1,10, and 100). Two types of boundary conditions have been considered. The first, when the inclined walls are heated with different uniform temperatures and the lower wall is insulated. The second, when the bottom wall is heated by applying a uniform heat flux while the inclined walls at

Nathaniel Hawthorne (1804-1864) has been widely known for his special interest in the female characters. In many of his novels, he narrates the conditions, values, and the institutions that surround and control the life of women, leading them to be victims. In “Rappaccini’s Daughter” (1844), the heroine, Beatrice is created to be victimized by her loved ones (her father and lover). This paper focuses on the term “victim,” it shows its aspects through the development of Beatrice’s character. The paper also studies a female character in the male-dominated society, to show the cruelty done to her, and how she is considered to be a second rate person, who is unable to live normally, or at least to save herself from dea