Informational videos are becoming increasingly important among all video types. The users spend so much time browsing the informative videos, even if they are not interested in all their topics. Thence, a new method for extracting descriptive frames is presented in this paper that allows users to navigate directly to the topics of their interest in the video. The proposed method consists of three main phases: video preprocessing, video segmentation, and the video separation phase. Firstly, frames are extracted from the videos, resized, and converted to grayscale. Then, the frames are divided into blocks, and the kurtosis moment is calculated for each block. The videos are segmented based on an examination of the differences between the features of the kurtosis moment. Lastly, the informative frames are grouped into a separate video after they are distinguished from the uninformative ones using the clustering technique. The results demonstrated the functional effectiveness of the proposed method. According to the accuracy and F1-Score measures, it has a performance of up to 100%. Moreover, the video is significantly summarized by reducing the duration to less than 1% of its original time.
Segmentation of real world images considered as one of the most challenging tasks in the computer vision field due to several issues that associated with this kind of images such as high interference between object foreground and background, complicated objects and the pixels intensities of the object and background are almost similar in some cases. This research has introduced a modified adaptive segmentation process with image contrast stretching namely Gamma Stretching to improve the segmentation problem. The iterative segmentation process based on the proposed criteria has given the flexibility to the segmentation process in finding the suitable region of interest. As well as, the using of Gamma stretching will help in separating the
... Show MoreThe economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s
... Show MoreAudio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to
... Show MoreIn this paper, some conditions to guarantee the existence of bounded solution to the second order multi delayed arguments differential equation are given. The Krasnoselskii theorem used to the Lebesgue’s dominated convergence and fixed point to obtain some new sufficient conditions for existence of solutions. Some important lemmas are established that are useful to prove the main results for oscillatory property. We also submitted some sufficient conditions to ensure the oscillation criteria of bounded solutions to the same equation.
This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa
... Show MoreThe present study focused mainly on the analysis of stiffened and unstiffened composite laminated plates subjected to buckling load. Analytical, numerical and experimental analysis for different cases has been considered. The experimental investigation is to manufacture the laminates and to find mechanical properties of glass-polyester such as longitudinal, transverse young modulus, shear modulus. The compressive test was carried to find the critical buckling load of plate. The design parameters of the laminates such as aspect ratio, thickness ratio, boundary conditions and number of stiffeners were investigated using high order shear deformation theory (HOST) and Finite element coded by ANSYS .The main conclusion was the buckling load c
... Show MoreHere, we found an estimation of best approximation of unbounded functions which satisfied weighted Lipschitz condition with respect to convex polynomial by means of weighted Totik-Ditzian modulus of continuity
A reduced-order extended state observer (RESO) based a continuous sliding mode control (SMC) is proposed in this paper for the tracking problem of high order Brunovsky systems with the existence of external perturbations and system uncertainties. For this purpose, a composite control is constituted by two consecutive steps. First, the reduced-order ESO (RESO) technique is designed to estimate unknown system states and total disturbance without estimating an available state. Second, the continuous SMC law is designed based on the estimations supplied by the RESO estimator in order to govern the nominal system part. More importantly, the robustness performance is well achieved by compensating not only the lumped disturbance, but also its esti
... Show MoreIn this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates
... Show MoreThis study is about the subject of exclusion of the application of foreign law as it violates the Islamic Sharia law in terms of Article (27) of the UAE Civil Transactions Law as amended in 2020, which before that date included all disputes involving a foreigner. According to the amendment referred to, the application of Islamic Sharia law shall be limited to civil transactions with the exclusion of personal status affairs.
The study concluded with many results, the most important of which is that the current text of Article (27) of the Civil Transactions Law as amended in 2020 is unable to explain what the judge may do in cases where the foreign law jurisdiction is referred to in one of the excluded texts, namely those related t
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