Reflections are ubiquitous effects in photos taken through transparent glass mediums, and represent a big problem in photography that impacts severely the performance of computer vision algorithms. Reflection removal is widely needed in daily lives with the prevalence of camera-equipped smart phones, and it is important, but it is a hard problem. This paper addresses the problem of reflection separation from two images taken from different viewpoints in front of a transparent glass medium, and proposes algorithm that exploits the natural image prior (gradient sparsity prior), and robust regression method to remove reflections. The proposed algorithm is tested on real world images, and the quantitative and visual quality comparisons were

The main goal of this work is study the land cover changes for "Baghdad city" over a period of (30) years using multi-temporal Landsat satellite images (TM, ETM+ and OLI) acquired in 1984, 2000, and 2015 respectively. In this work, The principal components analysis transform has been utilized as multi operators, (i.e. enhancement, compressor, and temporal change detector). Since most of the image band's information are presented in the first PCs image. Then, the PC1 image for all three years is partitioned into variable sized blocks using quad tree technique. Several different methods of classification have been used to classify Landsat satellite images; these are, proposed method singular value decomposition (SVD) using Visual Basic sof

In the present work, different remote sensing techniques have been used to analyze remote sensing data spectrally using ENVI software. The majority of algorithms used in the Spectral Processing can be organized as target detection, change detection and classification. In this paper several methods of target detection have been studied such as matched filter and constrained energy minimization.
The water body mapping have been obtained and the results showed changes on the study area through the period 1995-2000. Also the results that obtained from applying constrained energy minimization were more accurate than other method comparing with the real situation.

     In the task of detecting intrinsic plagiarism, the cases where reference corpus is absent are to be dealt with. This task is entirely based on inconsistencies within a given document. Detection of internal plagiarism has been considered as a classification problem. It can be estimated through taking into consideration self-based information from a given document.

The core contribution of the work proposed in this paper is associated with the document representation. Wherein, the document, also, the disjoint segments generated from it, have been represented as weight vectors demonstrating their main content. Where, for each element in these vectors, its average weight has been considered instead of its frequency.

Th

     Structure of network, which is known as community detection in networks, has received a great attention in diverse topics, including social sciences, biological studies, politics, etc. There are a large number of studies and practical approaches that were designed to solve the problem of finding the structure of the network. The definition of complex network model based on clustering is a non-deterministic polynomial-time hardness (NP-hard) problem. There are no ideal techniques to define the clustering. Here, we present a statistical approach based on using the likelihood function of a Stochastic Block Model (SBM). The objective is to define the general model and select the best model with high quality. Therefor

Early detection of eye diseases can forestall visual deficiency and vision loss. There are several types of human eye diseases, for example, diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. Diabetic retinopathy (DR) which is brought about by diabetes causes the retinal vessels harmed and blood leakage in the retina. Retinal blood vessels have a huge job in the detection and treatment of different retinal diseases. Thus, retinal vasculature extraction is significant to help experts for the finding and treatment of systematic diseases. Accordingly, early detection and consequent treatment are fundamental for influenced patients to protect their vision. The aim of this paper is to detect blood vessels from

Building Information Modeling (BIM) is extensively used in the construction industry due to its benefits throughout the Project Life Cycle (PLC). BIM can simulate buildings throughout PLC, detect and resolve problems, and improve building visualization that contributes to the representation of actual project details in the construction stage. BIM contributes to project management promotion by detecting problems that lead to conflicts, cost overruns, and time delays. This work aims to implement an effective BIM for the Iraqi construction projects’ life cycle. The methodology used is a literature review to collect the most important factors contributing to the success of BIM implementation, interview the team of the Cent

Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

The gravity and magnetic data of Tikrit-Kirkuk area in central Iraq were considered to study the tectonic situation in the area. The residual anomalies were separated from regional using space windows method with space of about 24, 12 and 10km to delineate the source level of the residual anomalies. The Total Horizontal Derivative (THD) is used to identify the fault trends in the basement and sedimentary rocks depending upon gravity and magnetic data. The identified faults in the study area show (NW-SE), less common (NE-SW) and rare (N-S) trends. Some of these faults extending from the basement to the upper most layer of the sedimentary rocks. It was found that the depth of some gravity and magnetic source range 12-13Km, which confirm th

This study successfully synthesized high-performance photodetectors based on Ag-WO3 core–shell heterostructures using a simple and economical two-step pulsed laser ablation in water method and has investigated the electrical characteristics of the Ag@WO3 nanocomposite heterojunction. The Hall effect tests indicate that the synthesized Ag@WO3 exhibits n-type conduction with a Hall mobility of 1.25 × 103 cm2V-1S-1. Dark current–voltage properties indicated that the created heterojunctions displayed rectification capabilities, with the highest rectification factor of around 1.71 seen at a 5 V bias. A photodetector’s responsivity reveals the existence of two response peaks, which are situated in the ultraviolet and visible region. The ph