The Determination of Dawn Time through Image Processing Camera

Determining the early time prayer is very fundamental for Muslims as it directly relates to the legal requirements of prayer. Prayers are not performed whenever we want, but rather there is a determination of the beginning and end of the prayer time as a guideline for Muslims to carry it out. The Indonesia government sets standards for Muslims to perform the dawn prayer service, by precisely determining the degree of the emergence of the dawn of Sadiq by -200. This study aims to compare the determination of the government's dawn time using different sensors, specifically drone cameras as image sensors. Drones were chosen due to their several advantages. The data generated by the drone is in the form of photos, which are subsequently processed using digital image processing software, called image-J. The data obtained are in the form of mean and standard deviation. All data collected in 1 day is recorded using Excel to form a graph of data which is then carried out by a polynomial approach to find out the cutoff point as the beginning of the dawn of Sadiq which indicates the start of dawn. The method used in this research is using the 4th order polynomial approach and the Sarrus method and the data obtained is the mean value and standard deviation. The conclusions obtained in the image analysis research are that the government's dawn time is 15 minutes too fast, the standard obtained in this study is -14.98° and unlike 2D SQM data, 3D drone data results in more accurate data analysis

Hierarchical Gaussian Scale-Space on Androgenic Hair Pattern Recognition

Androgenic hair pattern stated to be the new biometric trait since 2014. The research to improve the performance of androgenic hair pattern recognition system has begun to be developed due to the problems that occurred when other apparent biometric trait such as face is hidden from sight. The recognition system was built with hierarchical Gaussian scale-space using 4 octaves and 3 levels in each octave. The system also implemented the equalization process to adjust image’s intensity by using histogram equalization. We analyzed 400 images of androgenic hair in the database that were analyzed using 2-fold and 10-fold cross validation and Euclidean distance to classify it. The experimental results showed that our proposed method gave better performance compared to previous work that used Haar wavelet transformation and principal component analysis as the main method. The best recognition precision was 94.23 % obtained from the base octave with the third level using histogram equalization and 10-fold cross validation. 

Opposition effect on comet 67P/Churyumov-Gerasimenko using Rosetta-OSIRIS images

Aims. We aim to explore the behavior of the opposition effect as an important tool in optical remote sensing on the nucleus of comet 67P/Churyumov-Gerasimenko (67P), using Rosetta-OSIRIS images acquired in different filters during the approach phase, July-August 2014 and the close flyby images on 14 of February 2015, which contain the spacecraft shadow. Methods. We based our investigation on the global and local brightness from the surface of 67P with respect to the phase angle, also known as phase curve. The local phase curve corresponds to a region that is located at the Imhotep-Ash boundary of 67P. Assuming that the region at the Imhotep-Ash boundary and the entire nucleus have similar albedo, we combined the global and local phase curves to study the opposition-surge morphology and constrain the structure and properties of 67P. The model parameters were furthermore compared with other bodies in the solar system and existing laboratory study. Results. We found that the morphological parameters of the opposition surge decrease monotonically with wavelength, whereas in the case of coherent backscattering this behavior should be the reverse. The results from comparative analysis place 67P in the same category as the two Mars satellites, Phobos and Deimos, which are notably different from all airless bodies in the solar system. The similarity between the surface phase function of 67P and a carbon soot sample at extremely small angles is identified, introducing regolith at the boundary of the Imhotep-Ash region of 67P as a very dark and fluffy layer

Analysis of Land-Use and Land-Cover Changes in YongDeng County Using Remote Sensing and GIS

The research is supported by the fundamental Research Funds of Gansu Provincial Natural Science Fund of “Research on Land Use and Ecological Security in Ecologically Vulnerable Areas” (Project No. GSAN-ZL-2015-045) and Research on the Coordination Relationship between Land Urbanization and Population Urbanization (Project No. GSAU-ZL-2015-046). Abstract To generate reliable data on the spatiotemporal changes in land use and land cover in YongDeng county over a period of 24 years (1993 -2017) that will provide a basis for land use management decisions and policy formulation, this study used RS and GIS to analyze Landsat images of 1993, 2001, 2009 and 2017 of the study area which were acquired from the Geospatial Data Cloud (Http/westdc.westgis.ac.cn). Using supervised classification based on maximum likelihood classification method in ArcGIS (version 10.3) to classify images of the various years, the computed land use and land cover classes indicate that over the period of 24 years, significant Land use and land cover changes have occurred in the study area and the dominant land-use types in the study area were found to be grassland, bare land woodland and cultivated land occupying 65 percent, 20 percent, 8 percent and 6 percent of the study area respectively. As the years pass by, urban sprawl, population growth, agricultural activities, and other socio-economic activities in the study area, have led to rapid land-use transfer and change intensity. The results revealed that about 4.5 km² of grassland, 3.21 km² of bare land, 2.51 km² of cultivated lands and 1.7 km² of woodland were changed to construction lands from 1993-2017, whiles Cultivated lands, on the other hand, made gains of 2.56 km² from Garden lands, 2.3 km² from bare land and 1.05 km² from woodland from 1993 to 2017. Whiles transport land, from 1993 to 2017 gained 3.3 km² from bare land, 2.42 km² from grassland, and 1.32 km² from cultivated. Cultivated land, transportation land, construction land and water area and conservation land showed significantly positive land-use change intensity index of 2.19%, 1.97%, 1.49% and 1.31% respectively. Garden Land and woodland, though not significant also showed positive land-use change intensity of 0.55% and 0.79% respectively. The study identified population growth, urbanization and policy orientation as the main drivers of land use/land cover change in the area. The results reveal there is an urgent need to put measures in place to reduce the overexploitation of land in order to protect the integrity of biodiversity and to also ensure a continuous supply of valuable ecosystem services. Keywords: Land-use/land-cover change, remote sensing, geographical information system, dynamic change, YongDeng County. DOI: 10.7176/JEES/10-6-15 Publication date:June 30th 202

3D visualization of bioerosion in archaeological bone

Palaeoradiology is increasingly being used in archaeological and forensic sciences as a minimally invasive alternative to traditional histological methods for investigating bone microanatomy and its destruction by diagenetic processes. To better understand ancient mortuary practices, taphonomic studies using microCT scanning methods are gaining an ever more important role. Recently it was demonstrated that 2D virtual sections obtained by microCT scanning of intact samples are comparable to physical sections for the rating and diagnosis of bioerosion in archaeological bone. Importantly, volume image data obtained from tomographic methods also allow the rendering and analysis of 3D models. Building on these methods we provide (1) detailed descriptions of bioerosion in 3D volume renderings, virtual sections, and traditional micrographs, and (2) accessible techniques for the visualization of bioerosion in skeletal samples. The dataset is based on twenty-eight cortical bone samples, including twenty femora (of which five are cremated), two ribs, two parietals, one mandibular ramus, one humerus, and two faunal long bones from five archaeological sites in Lower Austria dating from the Early Neolithic to the Late Iron Age. Notably, we reduce the need for time-consuming image segmentation by sequentially applying two noise-reducing, edge-preserving filters, and using an image-display transfer function that visualizes bioerosion, as well as Haversian and Volkmann canal structure and density in 3D. In doing so we are also able to visualize in 3D the invasion of canals by microbiota, which has previously only been reported in 2D sections. Unlike conventional thin sections, the 3D volume images shown here are easy to create and interpret, even for archaeologists inexperienced in histology, and readily facilitate the illustration and communication of microtaphonomic effects

Automatic detection and quantification of abdominal aortic calcification in dual energy X-ray absorptiometry

Cardiovascular disease (CVD) is a major cause of mortality and the main cause of morbidity worldwide. CVD may lead to heart attacks and strokes and most of these are caused by atherosclerosis; this is a medical condition in which the arteries become narrowed and hardened due to an excessive build-up of plaque on the inner artery wall. Arterial calcification and, in particular, abdominal aortic calcification (AAC) is a manifestation of atherosclerosis and a prognostic indicator of CVD. In this paper, a two-stage automatic method to detect and quantify the severity of AAC is described; it is based on the analysis of lateral vertebral fracture assessment (VFA) images. These images were obtained on a dual energy x-ray absorptiometry (DXA) scanner used in single energy mode. First, an active appearance model was used to segment the lumbar vertebrae L1-L4 and the aorta on VFA images; the segmentation of the aorta was based on its position with respect to the vertebrae. In the second stage, feature vectors representing calcified regions in the aorta were extracted to quantify the severity of AAC. The presence and severity of AAC was also determined using an established visual scoring system (AC24). The abdominal aorta was divided into four parts immediately anterior to each vertebra, and the severity of calcification in the anterior and posterior walls was graded separately for each part on a 0-3 scale. The results were summed to give a composite severity score ranging from 0 to 24. This severity score was classified as follows: mild AAC (score 0-4), moderate AAC (score 5-12) and severe AAC (score 12-24). Two classification algorithms (k-nearest neighbour and support vector machine) were trained and tested to assign the automatically extracted feature vectors into the three classes. There was good agreement between the automatic and visual AC24 methods and the accuracy of the automated technique relative to visual classification indicated that it is capable of identifying and quantifying AAC over a range of severit

Биоимиджинг клеток: введение в анализ изображений с помощью ImageJ (Часть 1)

Пособие будет полезным для бакалавров, магистров и аспирантов при освоении ими программного комплекса ImageJ (Fiji) и получении первичных навыков анализа визуальных изображений в рамках проведения лабораторно-практических занятий, выполнения курсовых и дипломных проектов, кандидатских диссертаций, а также для научных работников, преподавателей вузов и специалистов, занимающихся компьютерной обработкой цифровых изображений микрообъектов в области клеточной биологии, цитофизиологии, биоимиджинговой информатики и др.2

Detection and Localization of Linear Features Based on Image Processing Methods

In this work, the general problem of the detection of features in images is considered. One of the methods, the orientation detection of lines, utilized the Radon transform (sinogram) of an image to detect lines at different angles in an image. The line thickness algorithm was generated by finding a pattern formed by particular lines in an image. The filtering of reconstructed images dealt with the removal of blur and other artifacts that arose in the course of inverting the Radon transform of an image to attempt to obtain the original image

The mathematical characteristic of the Laplace contour filters used in digital image processing. The third order filters

The Laplace operator is a differential operator which is used to detect edges of objects in digital images. This paper presents the properties of the most commonly used third-order 3x3 pixels Laplace contour filters including the difference schemes used to derive them. The authors focused on the mathematical properties of the Laplace filters. The basic reasons of the differences of the properties were studied and indicated using their transfer functions and modified differential equations. The relations between the transfer function for the differential Laplace operator and its difference operators were described and presented graphically. The impact of the corner elements of the masks on the results was discussed. This is a theoretical work. The basic research conducted here refers to a few practical examples which are illustrations of the derived conclusions.We are aware that unambiguous and even categorical final statements as well as indication of areas of the results application always require numerous experiments and frequent dissemination of the results. Therefore, we present only a concise procedure of determination of the mathematical properties of the Laplace contour filters matrices. In the next paper we shall present the spectral characteristic of the fifth order filters of the Laplace type