Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOMs). Therefore, finding a fast PET classification method that accurately classify image pattern is crucial. To this end, this paper proposes a new scheme for accurate and fast image pattern classification using an efficient DOM. To reduce the computational complexity of feature extraction, an election mechanism is proposed to reduce the number of processed block patterns. In addition, support vector machine is used to classify the extracted features for different block patterns. The proposed scheme is evaluated by comparing the accuracy of the proposed method with the accuracy achieved by state-of-the-art methods. In addition, we compare the performance of the proposed method based on different DOMs to get the robust one. The results show that the proposed method achieves the highest classification accuracy compared with the existing methods in all the scenarios considered.
Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or
... Show MoreAbstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to
... Show MoreHealthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
... Show MoreNuclear structure of 20,22Ne isotopes has been studied via the shell model with Skyrme-Hartree-Fock calculations. In particular, the transitions to the low-lying positive and negative parity excited states have been investigated within three shell model spaces; sd for positive parity states, spsdpf large-basis (no-core), and zbme model spaces for negative parity states. Excitation energies, reduced transition probabilities, and elastic and inelastic form factors were estimated and compared to the available experimental data. Skyrme interaction was used to generate a one-body potential in the Hartree-Fock calculations for each selected excited states, which is then used to calculate the single-particle matrix elements. Skyrme interac
... Show MoreBipedal robotic mechanisms are unstable due to the unilateral contact passive joint between the sole and the ground. Hierarchical control layers are crucial for creating walking patterns, stabilizing locomotion, and ensuring correct angular trajectories for bipedal joints due to the system’s various degrees of freedom. This work provides a hierarchical control scheme for a bipedal robot that focuses on balance (stabilization) and low-level tracking control while considering flexible joints. The stabilization control method uses the Newton–Euler formulation to establish a mathematical relationship between the zero-moment point (ZMP) and the center of mass (COM), resulting in highly nonlinear and coupled dynamic equations. Adaptiv
... Show MoreA strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as
... Show MoreIn the early 90s military operations and United Nations Special Commission “UNSCOM” teams have been destroyed the past Iraqi chemical program. Both operations led an extensive number of scattered remnants of contaminated areas. The quantities of hazardous materials, incomplete destructed materials, and toxic chemicals were sealed in two bunkers. Deficiency of appropriate destruction technology led to spreading the contamination around the storage site. This paper aims to introduce the environmental detection of the contamination in the storage site area using geospatial analysis technique. The environmental contamination level of nutrients and major ions such as sulphate (SO4), potassium (K), sodium (Na), magnesi
... Show MoreGraphene oxide (GO) was prepared from graphite (GT) with Hammer method, the GO was reduced with hydrazine hydrate to produce a reduced graphene oxide (RGO). The RGO was reacted with thiocarbohydrazide (TCH) to functionalize the RGO with 4-amino-3-symbol-1h-1, 2, 4-triazol-5 (4H) –thion group and to obtain (RGOT). All the prepared nanomaterial and the product of the functionalization RGOT were characterized with Fourier transformer infrared (FT-IR) spectroscopy, X-ray diffraction (XRD) analysis. RGOT mixed with ultrasonic device at different pH values of phosphate buffer solution (PBS), the mixture used to modifying a screen printed carbon electrodes SPCE and with cyclic voltammetry the sensitivity of selectivity of the new modifying elect
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