Automatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used in this field of study. The literature has reported that the conditions for training and testing are highly correlated. Taken together, these facts support strong recommendations for using MFCC features in similar environmental conditions (train/test) for speaker recognition. However, with noise and reverberation present, MFCC performance is not reliable. To address this, we propose a new feature 'entrocy' for accurate and robust speaker recognition, which we mainly employ to support MFCC coefficients in noisy environments. Entrocy is the fourier transform of the entropy, a measure of the fluctuation of the information in sound segments over time. Entrocy features are combined with MFCCs to generate a composite feature set which is tested using the gaussian mixture model (GMM) speaker recognition method. The proposed method shows improved recognition accuracy over a range of signal-to-noise ratios.
Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.
The main targets for using the edge detection techniques in image processing are to reduce the number of features and find the edge of image based-contents. In this paper, comparisons have been demonstrated between classical methods (Canny, Sobel, Roberts, and Prewitt) and Fuzzy Logic Technique to detect the edges of different samples of image's contents and patterns. These methods are tested to detect edges of images that are corrupted with different types of noise such as (Gaussian, and Salt and pepper). The performance indices are mean square error and peak signal to noise ratio (MSE and PSNR). Finally, experimental results show that the proposed Fuzzy rules and membership function provide better results for both noisy and noise-free
... Show MoreAs one type of resistance furnace, the electrical tube furnace (ETF) typically experiences input noise, measurement noise, system uncertainties, unmodeled dynamics and external disturbances, which significantly degrade its temperature control performance. To provide precise, and robust temperature tracking performance for the ETF, a robust composite control (RCC) method is proposed in this paper. The overall RCC method consists of four elements: First, the mathematical model of the ETF system is deduced, then a state feedback control (SFC) is constructed. Third, a novel disturbance observer (DO) is designed to estimate the lumped disturbance with one observer parameter. Moreover, the stability of the closed loop system including controller
... Show MoreIn this research we will present the signature as a key to the biometric authentication technique. I shall use moment invariants as a tool to make a decision about any signature which is belonging to the certain person or not. Eighteen voluntaries give 108 signatures as a sample to test the proposed system, six samples belong to each person were taken. Moment invariants are used to build a feature vector stored in this system. Euclidean distance measure used to compute the distance between the specific signatures of persons saved in this system and with new sample acquired to same persons for making decision about the new signature. Each signature is acquired by scanner in jpg format with 300DPI. Matlab used to implement this system.
Classical cryptography systems exhibit major vulnerabilities because of the rapid development of quan tum computing algorithms and devices. These vulnerabilities were mitigated utilizing quantum key distribution (QKD), which is based on a quantum no-cloning algorithm that assures the safe generation and transmission of the encryption keys. A quantum computing platform, named Qiskit, was utilized by many recent researchers to analyze the security of several QKD protocols, such as BB84 and B92. In this paper, we demonstrate the simulation and implementation of a modified multistage QKD protocol by Qiskit. The simulation and implementation studies were based on the “local_qasm” simulator and the “FakeVigo” backend, respectively. T
... Show MoreThe automatic estimation of speaker characteristics, such as height, age, and gender, has various applications in forensics, surveillance, customer service, and many human-robot interaction applications. These applications are often required to produce a response promptly. This work proposes a novel approach to speaker profiling by combining filter bank initializations, such as continuous wavelets and gammatone filter banks, with one-dimensional (1D) convolutional neural networks (CNN) and residual blocks. The proposed end-to-end model goes from the raw waveform to an estimated height, age, and gender of the speaker by learning speaker representation directly from the audio signal without relying on handcrafted and pre-computed acou
... Show MoreThe fact that the signature is widely used as a means of personal verification
emphasizes the need for an automatic verification system. Verification can be
performed either Offline or Online based on the application. Offline systems work on
the scanned image of a signature. In this paper an Offline Verification of handwritten
signatures which use set of simple shape based geometric features. The features used
are Mean, Occupancy Ratio, Normalized Area, Center of Gravity, Pixel density,
Standard Deviation and the Density Ratio. Before extracting the features,
preprocessing of a scanned image is necessary to isolate the signature part and to
remove any spurious noise present. Features Extracted for whole signature
Image content verification is to confirm the validity of the images, i.e. . To test if the image has experienced any alteration since it was made. Computerized watermarking has turned into a promising procedure for image content verification in light of its exceptional execution and capacity of altering identification.
In this study, a new scheme for image verification reliant on two dimensional chaotic maps and Discrete Wavelet Transform (DWT) is introduced. Arnold transforms is first applied to Host image (H) for scrambling as a pretreatment stage, then the scrambled host image is partitioned into sub-blocks of size 2×2 in which a 2D DWT is utilized on ea
... Show MoreWhen laser light incident on biological tissue, it is either reflected from the
surface of the tissue (e.g. the skin) or scattered inside the tissue or absorbed .The laser light will be
absorbed by water, hemoglobin and melanin. Absorption is also highly dependent on wave-length of
laser radiation. The absorbed light is converted into kinetic energy leading to laser effect that when
appropriately applied can produce reaction ranging from incision, vaporization to coagulation. Aim of
the study: To evaluate the efficiency of diode Laser 810 ± 20nm in treatment of oral lesions. Methods:
6 patients (2 females and 4 males) with different oral lesions were treated in the hospital of specialized
surgeries by the use of dio
Recent studies have proved the important role of fungi in the biodegradation of oil pollutants. The present study aims to find the optimal conditions for the fungi to get the best rate of the biodegradation of the polycyclic aromatic hydrocarbon (PAHs) (Naphthalene) compounds. Soil samples were taken from 18 different sites polluted with oil wastes and cultured then obtained 312 isolated fungi from 64 replicates Primarily screening were done on fungal isolates on solid media containing naphthalene the results revealed that 25 fungal isolates gave good growth, 47 fungal isolates gave Moderate growth, 66 gave weak growth and 147 fungal isolates gave no growth on Naphthalene solid media.
Then secondary screening were done on 25 fungal is