Search results for: single image super resolution

Authors: Anatoly D. Pluzhnikov, Elena N. Pribludova, Alexander G. Ryndyk

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In conjunction with the problem of the target selection on a clutter background, the analysis of the scanning rate influence on the spatial-temporal signal structure, the generalized multivariate correlation function and the quality of the resolution with the increase pulse repetition frequency is made. The possibility of the object space-distance resolution, which is conditioned by the range-to-angle conversion with an increased scanning rate, is substantiated. The calculations for the real cylindrical array at high scanning rate are presented. The high scanning rate let to get the signal to noise improvement of the order of 10 dB for the space-time signal processing.

Keywords: antenna pattern, array, signal processing, spatial resolution

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Authors: Kindeye Fenta Mekonnen, Alagaw Ababu Kifle

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The failure of international responses to armed conflict to address local preconditions for national stability has recently attracted what has been called the ‘local turn’ in peace building. This ‘local turn’ in peace building amplified a renewed interest in traditional/indigenous methods of conflict resolution, a field that has been hitherto dominated by anthropologists with their focus on the procedures and rituals of such approaches. This notwithstanding, there is still limited empirical work on the relevance of traditional methods of conflict resolution to end localized conflicts vis-à-vis hybrid and modern approaches. The few exceptions to this generally draw their conclusion from very few (almost all successful) cases that make it difficult to judge the validity and cross-case application of their results. This paper seeks to fill these gaps by undertaking a quantitative analysis of the trend and applications of different communal conflict resolution initiatives, their potential to usher in long-term peace, and the extent to which their outcomes are influenced by the intensity and scope of a conflict. The paper makes the following three tentative conclusions. First, traditional mechanisms and traditional actors still dominate the communal conflict resolution landscape, either individually or in combination with other methods. Second, traditional mechanisms of conflict resolution tend to be more successful in ending a conflict and preventing its re-occurrence compared to hybrid and modern arrangements. This notwithstanding and probably due to the scholarly call for local turn in peace building, contemporary communal conflict resolution approaches are becoming less and less reliant on traditional mechanisms alone and (therefore) less effective. Third, there is yet inconclusive evidence on whether hybridization is an asset or a liability in the resolution of communal conflicts and the extent to which this might be mediated by the intensity of a conflict.

Keywords: traditional conflict resolution, hybrid conflict resolution, communal conflict, relevance, conflict intensity

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Authors: Vishal V. R. Nandigana, Mohammad Heiranian, Narayana R. Aluru

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Graphene material has found tremendous applications in water desalination, DNA sequencing and energy storage. Multiple nanopores are etched to create opening for water desalination and energy storage applications. The nanopores created are of the order of 3-5 nm allowing multiple ions to transport through the pore. In this paper, we present for the first time, molecular dynamics study of single ion transport, where only one ion passes through the graphene nanopore. The diameter of the graphene nanopore is of the same order as the hydration layers formed around each ion. Analogous to single electron transport resulting from ionic transport is observed for the first time. The current-voltage characteristics of such a device are similar to single electron transport in quantum dots. The current is blocked until a critical voltage, as the ions are trapped inside a hydration shell. The trapped ions have a high energy barrier compared to the applied input electrical voltage, preventing the ion to break free from the hydration shell. This region is called “Coulomb blockade region”. In this region, we observe zero transport of ions inside the nanopore. However, when the electrical voltage is beyond the critical voltage, the ion has sufficient energy to break free from the energy barrier created by the hydration shell to enter into the pore. Thus, the input voltage can control the transport of the ion inside the nanopore. The device therefore acts as a binary storage unit, storing 0 when no ion passes through the pore and storing 1 when a single ion passes through the pore. We therefore postulate that the device can be used for fluidic computing applications in chemistry and biology, mimicking a computer. Furthermore, the trapped ion stores a finite charge in the Coulomb blockade region; hence the device also acts a super capacitor.

Keywords: graphene nanomembrane, single ion transport, Coulomb blockade, nanofluidics

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

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Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel .The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. The proposed method achieves pixel level parallelism as well as image level parallelism.

Keywords: edge detection, multicore, gpu, opencl, mpi

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Authors: Alper Cumhur, Hasan Baylavlı, Eren Gödek

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Use of superplasticity chemical admixtures in concrete production is widespread all over the world and has become almost inevitable. Super-plasticizers (SPA), extend the setting time of concrete by adsorbing onto cement particles and provide concrete to preserve its fresh state workability properties. Hyper-plasticizers (HPA), as a special type of superplasticizer, provide the production of qualified concretes by increasing the workability properties of concrete, effectively. However, compatibility of cement with super and hyper-plasticizers is quite important for achieving efficient workability in order to produce qualified concretes. In 2011, the EN 197-1 standard is edited and cement classifications were updated. In this study, the compatibility of hyper-plasticizer and CEM I SR0 type sulphate resisting cement (SRC) that firstly classified in EN 197-1 is investigated. Within the scope of the experimental studies, a reference cement mortar was designed with a water/cement ratio of 0.50 confirming to EN 196-1. Fresh unit density of mortar was measured and spread diameters (at 0, 60, 120 min after mix preparation) and setting time of reference mortar were determined with flow table and Vicat tests, respectively. Three mortars are being re-prepared with using both super and hyper-plasticizer confirming to ASTM C494 by 0.50, 0.75 and 1.00% of cement weight. Fresh unit densities, spread diameters and setting times of super and hyper plasticizer added mortars (SPM, HPM) will be determined. Theoretical air-entrainment values of both SPMs and HPMs will be calculated by taking the differences between the densities of plasticizer added mortars and reference mortar. The flow table and Vicat tests are going to be repeated to these mortars and results will be compared. In conclusion, compatibility of SRC with SPA and HPA will be investigated. It is expected that optimum dosages of SPA and HPA will be determined for providing the required workability and setting conditions of SRC mortars, and the advantages/disadvantages of both SPA and HPA will be discussed.

Keywords: CEM I SR0, hyper-plasticizer, setting time, sulphate resisting cement, super-plasticizer, workability

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Authors: N. Reichbach, A. Kuperman

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The paper describes a design of a monitoring system for super capacitor packs in propulsion systems, allowing determining the instantaneous energy capacity under power loading. The system contains real-time recursive-least-squares identification mechanism, estimating the values of pack capacitance and equivalent series resistance. These values are required for accurate calculation of the state-of-energy.

Keywords: real-time monitoring, RLS identification algorithm, state-of-energy, super capacitor

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Authors: Gurinder Singh, Kulbir Singh

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Digital multimedia contents such as image, video, and audio can be tampered easily due to the availability of powerful editing softwares. Multimedia forensics is devoted to analyze these contents by using various digital forensic techniques in order to validate their authenticity. Digital image forensics is dedicated to investigate the reliability of digital images by analyzing the integrity of data and by reconstructing the historical information of an image related to its acquisition phase. In this paper, a survey is carried out on the forgery detection by considering the most recent and promising digital image forensic techniques.

Keywords: Computer Forensics, Multimedia Forensics, Image Ballistics, Camera Source Identification, Forgery Detection

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Authors: M. Brik, S. Harmand, I. Zaaroura

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This report, an experimental investigation, concerns the sessile daughter drop remaining during the coalescence of water drops in a liquid-liquid (LL) system. The two drops are initially vertically aligned where the sessile drop is deposited on a chemically treated super-hydrophobic surface of a cube fill of silicone oil. In order to analyze the coalescence dynamics, a series of experiments have been performed using a generation droplets system (KRUSS) that measures contact angles as well coupled with a high-speed camera (Keyence VW-9000E) to record the process at a frame rate of 15000s-1. It’s depicted that in such configuration, the head drop volume has a primordial impact on the dynamics of the coalescence process, especially at the last stage. It’s found that for a sessile drop deposited on a super-hydrophobic surface, where the contact angle is about θ ≈ 145°, the coalescence process is remarked to be complete without any recoiling of the coalesced drop or a generation of a sessile daughter drop at the super-hydrophobic surface when the head drop volume is small enough (Vₐᵦ< Vₛ up to Vₐᵦ = 3Vₛ). On the other side, the coalescence process starts to be followed by jumping off the resulted drop as well as a remaining of a small sessile daughter drop on the bottom surface of the cube from a head drop volume Vₐᵦ of about 4 times than that of the sessile drop Vₛ.

Keywords: drops coalescence, dispersed multiphase flow, drops dynamics, liquid-liquid system

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Authors: Roza Afarin, Saeed Mozaffari

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The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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Authors: R. K. Pateriya, Jyoti Bharti

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This paper presents an approach for data hiding methods which provides a secret communication between sender and receiver. The data is hidden in gray-scale images and the boundary of gray-scale image is used to store the mapping information. In this an approach data is in ASCII format and the mapping is in between ASCII value of hidden message and pixel value of cover image, since pixel value of an image as well as ASCII value is in range of 0 to 255 and this mapping information is occupying only 1 bit per character of hidden message as compared to 8 bit per character thus maintaining good quality of stego image.

Keywords: ASCII value, cover image, PSNR, pixel value, stego image, secret message

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Authors: Salim H. Al Salmani, Kevin Tansey, Mohammed S. Ozigis

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The study of the growth of built-up areas and settlement expansion is a major exercise that city managers seek to undertake to establish previous and current developmental trends. This is to ensure that there is an equal match of settlement expansion needs to the appropriate levels of services and infrastructure required. This research aims at demonstrating the potential of satellite image processing technique, harnessing the utility of single feature probability-object based image analysis technique in assessing the urban growth dynamics of the Muscat Governorate in Oman for the period 1990, 2002 and 2013. This need is fueled by the continuous expansion of the Muscat Governorate beyond predicted levels of infrastructural provision. Landsat Images of the years 1990, 2002 and 2013 were downloaded and preprocessed to forestall appropriate radiometric and geometric standards. A novel approach of probability filtering of the target feature segment was implemented to derive the spatial extent of the final Built-Up Area of the Muscat governorate for the three years period. This however proved to be a useful technique as high accuracy assessment results of 55%, 70%, and 71% were recorded for the Urban Landcover of 1990, 2002 and 2013 respectively. Furthermore, the Normalized Differential Built – Up Index for the various images were derived and used to consolidate the results of the SFP-OBIA through a linear regression model and visual comparison. The result obtained showed various hotspots where urbanization have sporadically taken place. Specifically, settlement in the districts (Wilayat) of AL-Amarat, Muscat, and Qurayyat experienced tremendous change between 1990 and 2002, while the districts (Wilayat) of AL-Seeb, Bawshar, and Muttrah experienced more sporadic changes between 2002 and 2013.

Keywords: urban growth, single feature probability, object based image analysis, landcover change

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Authors: Ouafa Benaida, Abdelhamid Loukil, Adda Ali Pacha

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In recent years, the growing interest of scientists in the field of image processing and analysis of underwater images and videos has been strengthened following the emergence of new underwater exploration techniques, such as the emergence of autonomous underwater vehicles and the use of underwater image sensors facilitating the exploration of underwater mineral resources as well as the search for new species of aquatic life by biologists. Indeed, underwater images and videos have several defects and must be preprocessed before their analysis. Underwater landscapes are usually darkened due to the interaction of light with the marine environment: light is absorbed as it travels through deep waters depending on its wavelength. Additionally, light does not follow a linear direction but is scattered due to its interaction with microparticles in water, resulting in low contrast, low brightness, color distortion, and restricted visibility. The improvement of the underwater image is, therefore, more than necessary in order to facilitate its analysis. The research presented in this paper aims to implement and evaluate a set of classical techniques used in the field of improving the quality of underwater images in several color representation spaces. These methods have the particularity of being simple to implement and do not require prior knowledge of the physical model at the origin of the degradation.

Keywords: underwater image enhancement, histogram normalization, histogram equalization, contrast limited adaptive histogram equalization, single-scale retinex

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Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: M. Najafi, S. Bab, F. Rahimi Dehgolan

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The motion of an axially moving beam with rotating prismatic joint with a tip mass on the end is analyzed to investigate the nonlinear vibration and dynamic stability of the beam. The beam is moving with a harmonic axially and rotating velocity about a constant mean velocity. A time-dependent partial differential equation and boundary conditions with the aid of the Hamilton principle are derived to describe the beam lateral deflection. After the partial differential equation is discretized by the Galerkin method, the method of multiple scales is applied to obtain analytical solutions. Frequency response curves are plotted for the super harmonic resonances of the first and the second modes. The effects of non-linear term and mean velocity are investigated on the steady state response of the axially moving beam. The results are validated with numerical simulations.

Keywords: super harmonic resonances, non-linear vibration, axially moving beam, Galerkin method

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Authors: Aayushi Pandey, Manoj Kumar Pandey, Ashutosh Tiwari, Kireet Kumar

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Glaciers play an important role in climate change and are sensitive phenomena of global climate change scenario. Glaciers in Himalayas are unique as they are predominantly valley type and are located in tropical, high altitude regions. These glaciers are often covered with debris which greatly affects ablation rate of glaciers and work as a sensitive indicator of glacier health. The aim of this study is to map high altitude Glacier surface with a focus on glacial lake and debris estimation using different techniques in Nagling glacier of dhauliganga basin in Himalayan region. Different Image Classification techniques i.e. thresholding on different band ratios and supervised classification using maximum likelihood classifier (MLC) have been used on high resolution sentinel 2A level 1c satellite imagery of 14 October 2017.Here Near Infrared (NIR)/Shortwave Infrared (SWIR) ratio image was used to extract the glaciated classes (Snow, Ice, Ice Mixed Debris) from other non-glaciated terrain classes. SWIR/BLUE Ratio Image was used to map valley rock and Debris while Green/NIR ratio image was found most suitable for mapping Glacial Lake. Accuracy assessment was performed using high resolution (3 meters) Planetscope Imagery using 60 stratified random points. The overall accuracy of MLC was 85 % while the accuracy of Band Ratios was 96.66 %. According to Band Ratio technique total areal extent of glaciated classes (Snow, Ice ,IMD) in Nagling glacier was 10.70 km2 nearly 38.07% of study area comprising of 30.87 % Snow covered area, 3.93% Ice and 3.27 % IMD covered area. Non-glaciated classes (vegetation, glacial lake, debris and valley rock) covered 61.93 % of the total area out of which valley rock is dominant with 33.83% coverage followed by debris covering 27.7 % of the area in nagling glacier. Glacial lake and Debris were accurately mapped using Band ratio technique Hence, Band Ratio approach appears to be useful for the mapping of debris covered glacier in Himalayan Region.

Keywords: band ratio, Dhauliganga basin, glacier mapping, Himalayan region, maximum likelihood classifier (MLC), Sentinel-2 satellite image

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Authors: Lindani Mbatha, Suvendi Rimer, Mpho Gololo

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Image segmentation is the process of dividing an image into several sections, such as the object's background and the foreground. It is a critical technique in both image-processing tasks and computer vision. Most of the image segmentation algorithms have been developed for gray-scale images and little research and algorithms have been developed for the color images. Most image segmentation algorithms or techniques vary based on the input data and the application. Nearly all of the techniques are not suitable for noisy environments. Most of the work that has been done uses the Markov Random Field (MRF), which involves the computations and is said to be robust to noise. In the past recent years' image segmentation has been brought to tackle problems such as easy processing of an image, interpretation of the contents of an image, and easy analysing of an image. This article reviews and summarizes some of the image segmentation techniques and algorithms that have been developed in the past years. The techniques include neural networks (CNN), edge-based techniques, region growing, clustering, and thresholding techniques and so on. The advantages and disadvantages of medical ultrasound image segmentation techniques are also discussed. The article also addresses the applications and potential future developments that can be done around image segmentation. This review article concludes with the fact that no technique is perfectly suitable for the segmentation of all different types of images, but the use of hybrid techniques yields more accurate and efficient results.

Keywords: clustering-based, convolution-network, edge-based, region-growing

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Authors: Hooman Torabifard

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In the last few years, with the progress of technology and computers and artificial intelligence entry into all kinds of scientific and industrial fields, the lifestyles of human life have changed and in general, the way of humans live on earth has many changes and development. Until now, some of the changes has occurred in the context of digital images and image processing and still continues. However, besides all the benefits, there have been disadvantages. One of these disadvantages is the multiplicity of images with high volume and data; the focus of this paper is on improving and developing a method for summarizing and enhancing the productivity of these images. The general method used for this purpose in this paper consists of a set of methods based on data obtained from image processing and using the PSO (Particle swarm optimization) algorithm. In the remainder of this paper, the method used is elaborated in detail.

Keywords: image summarization, particle swarm optimization, image threshold, image processing

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Authors: Mohamed A. Almoghalis, Osman M. Hegazy, Ibrahim F. Imam, Ali H. Elbastawessy

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This paper presents a new hyperspectral image segmentation scheme with respect to both spatial and spectral contexts. The scheme uses the 8-pixels spatial pattern to build a weight structure that holds the number of outlier bands for each pixel among its neighborhood windows in different directions. The number of outlier bands for a pixel is obtained using bands quartile box plots profile among spatial 8-pixels pattern windows. The quartile box plot weight structure represents the spatial-spectral context in the image. Instead of starting segmentation process by single pixels, the proposed methodology starts by pixels groups that proved to share the same spectral features with respect to their spatial context. As a result, the segmentation scheme starts with Jigsaw pieces that build a mosaic image. The following step builds a model for each Jigsaw piece in the mosaic image. Each Jigsaw piece will be merged with another Jigsaw piece using KNN applied to their bands' quartile box plots profiles. The scheme iterates till required number of segments reached. Experiments use two data sets obtained from Earth Observer 1 (EO-1) sensor for Egypt and France. Initial results qualitative analysis showed encouraging results compared with ground truth. Quantitative analysis for the results will be included in the final paper.

Keywords: hyperspectral image segmentation, image processing, remote sensing, box plot

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Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

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Authors: Khalid A. Al-Afandy, El-Sayyed El-Rabaie, Osama Salah, Ahmed El-Mhalaway

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This paper presents a high secure data hiding technique using image cropping and Least Significant Bit (LSB) steganography. The predefined certain secret coordinate crops will be extracted from the cover image. The secret text message will be divided into sections. These sections quantity is equal the image crops quantity. Each section from the secret text message will embed into an image crop with a secret sequence using LSB technique. The embedding is done using the cover image color channels. Stego image is given by reassembling the image and the stego crops. The results of the technique will be compared to the other state of art techniques. Evaluation is based on visualization to detect any degradation of stego image, the difficulty of extracting the embedded data by any unauthorized viewer, Peak Signal-to-Noise Ratio of stego image (PSNR), and the embedding algorithm CPU time. Experimental results ensure that the proposed technique is more secure compared with the other traditional techniques.

Keywords: steganography, stego, LSB, crop

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Authors: K. Suganya Devi, P. Srinivasan, M. P. Vaishnave, G. Arutperumjothi

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Today’s internet world is highly prone to various online attacks, of which the most harmful attack is phishing. The attackers host the fake websites which are very similar and look alike. We propose an image based authentication using steganography and visual cryptography to prevent phishing. This paper presents a secure steganographic technique for true color (RGB) images and uses Discrete Cosine Transform to compress the images. The proposed method hides the secret data inside the cover image. The use of visual cryptography is to preserve the privacy of an image by decomposing the original image into two shares. Original image can be identified only when both qualified shares are simultaneously available. Individual share does not reveal the identity of the original image. Thus, the existence of the secret message is hard to be detected by the RS steganalysis.

Keywords: image security, random LSB, steganography, visual cryptography

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Authors: Nabilah Ibrahim, Hafiz Mohd Zaini, Wan Fatin Liyana Mutalib

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Ultrasound equipment or machine is capable to scan in two dimensional (2D) areas. However there are some limitations occur during scanning an object. The problem will occur when scanning process that involving the asymmetric object. In this project, the ultrasound probe holder for asymmetric reflector scanning in 3D image is proposed to make easier for scanning the phantom or object that has asymmetric shape. Initially, the constructed asymmetric phantom that construct will be used in 2D scanning. Next, the asymmetric phantom will be interfaced by the movement of ultrasound probe holder using the Arduino software. After that, the performance of the ultrasound probe holder will be evaluated by using the various asymmetric reflector or phantom in constructing a 3D image

Keywords: ultrasound 3D images, axial and lateral resolution, asymmetric reflector, Arduino software

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Authors: Minakshi Mainaji Sonawane, Bharti W. Gawali, Sudhir Mendhekar, Ramesh R. Manza

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People's lives and health are severely impacted by skin diseases. A new study proposes an effective method for identifying the different forms of skin diseases. Image denoising is a technique for improving image quality after it has been harmed by noise. The proposed technique is based on the usage of the wavelet transform. Wavelet transform is the best method for analyzing the image due to the ability to split the image into the sub-band, which has been used to estimate the noise ratio at the noisy image. According to experimental results, the proposed method presents the best values for MSE, PSNR, and Entropy for denoised images. we can found in Also, by using different types of wavelet transform filters is make the proposed approach can obtain the best results 23.13, 20.08, 50.7 for the image denoising process

Keywords: MSE, PSNR, entropy, Gaussian filter, DWT

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Authors: W. R. M. Shehani Shanika

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Selling goods and services using images, names and personalities of celebrities has become a common marketing strategy identified in modern physical and online markets. Two concepts called globalization and open economy have given numerous reasons to develop businesses to earn higher profits. Therefore, global market plus domestic markets in various countries have vigorously endorsing images of famous sport stars, film stars, singing stars and cartoon characters for the purpose of increasing demand for goods and services rendered by them. It has been evident that these trade strategies have become a threat to famous personalities in financially and personally. Right to the image is a basic human right which celebrities owned to avoid themselves from various commercial exploitations. In this respect, this paper aims to assess whether the law relating to character merchandising satisfactorily protects right to image of celebrities. However, celebrities can decide how much they receive for each representation to the general public. Simply they have exclusive right to decide monetary value for their image. But most commonly every country uses law relating to unfair competition to regulate matters arise thereof. Legal norms in unfair competition are not enough to protect image of celebrities. Therefore, celebrities must be able to avoid unauthorized use of their images for commercial purposes by fraudulent traders and getting unjustly enriched, as their images have economic value. They have the right for use their image for any commercial purpose and earn profits. Therefore it is high time to recognize right to image as a new dimension to be protected in the legal framework of character merchandising. Unfortunately, to the author’s best knowledge there are no any uniform, single international standard which recognizes right to the image of celebrities in the context of character merchandising. The paper identifies it as a controversial legal barrier faced by celebrities in the rapidly evolving marketplace. Finally, this library-based research concludes with proposals to ensure the right to image more broadly in the legal context of character merchandising.

Keywords: brand endorsement, celebrity, character merchandising, intellectual property rights, right to image, unfair competition

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Authors: Mamadou I. Wade, Henry C. Ogworonjo, Madiha Gul, Mandoye Ndoye, Mohamed Chouikha, Wayne Patterson

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In this paper, we present a novel application of the Paillier cryptographic system to the encryption of RGB (Red Green Blue) images. In this method, an RGB image is first separated into its constituent channel images, and the Paillier encryption function is applied to each of the channels pixel intensity values. Next, the encrypted image is combined and compressed if necessary before being transmitted through an unsecured communication channel. The transmitted image is subsequently recovered by a decryption process. We performed a series of security and performance analyses to the recovered images in order to verify their robustness to security attack. The results show that the proposed image encryption scheme produces highly secured encrypted images.

Keywords: image encryption, Paillier cryptographic system, RBG image encryption, Paillier

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Authors: Chin-Chen Chang, I-Ta Lee, Tsung-Ta Ke, Wen-Kai Tai

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Common methods for resizing image size include scaling and cropping. However, these two approaches have some quality problems for reduced images. In this paper, we propose an image resizing algorithm by separating the main objects and the background. First, we extract two feature maps, namely, an enhanced visual saliency map and an improved gradient map from an input image. After that, we integrate these two feature maps to an importance map. Finally, we generate the target image using the importance map. The proposed approach can obtain desired results for a wide range of images.

Keywords: energy map, visual saliency, gradient map, seam carving

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Authors: K. M. Alsager, N. O. Alshehri

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In this paper, we proposed the notion of single valued neutrosophic hesitant fuzzy rough set, by combining single valued neutrosophic hesitant fuzzy set and rough set. The combination of single valued neutrosophic hesitant fuzzy set and rough set is a powerful tool for dealing with uncertainty, granularity and incompleteness of knowledge in information systems. We presented both definition and some basic properties of the proposed model. Finally, we gave a general approach which is applied to a decision making problem in disease diagnoses, and demonstrated the effectiveness of the approach by a numerical example.

Keywords: single valued neutrosophic fuzzy set, single valued neutrosophic fuzzy hesitant set, rough set, single valued neutrosophic hesitant fuzzy rough set

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Authors: Rajashree Naik, Laxmi Kant Sharma

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Sambhar lake is the largest inland Salt Lake of India, declared as a Ramsar site on 23 March 1990. Due to high salinity and alkalinity condition its biodiversity richness is contributed by haloalkaliphilic flora and fauna along with the diverse land cover including waterbody, wetland, salt crust, saline soil, vegetation, scrub land and barren land which welcome large number of flamingos and other migratory birds for winter harboring. But with the gradual increase in the irrational salt extraction activities, the ecological diversity is at stake. There is an urgent need to assess the ecosystem. Advanced technology like remote sensing and GIS has enabled to look into the past, compare with the present for the future planning and management of the natural resources in a judicious way. This paper is a research work intended to present a vegetation in typical inland lake environment of Sambhar wetland using satellite data of NASA’s EO-1 Hyperion sensor launched in November 2000. With the spectral range of 0.4 to 2.5 micrometer at approximately 10nm spectral resolution with 242 bands 30m spatial resolution and 705km orbit was used to produce a vegetation map for a portion of the wetland. The vegetation map was tested for classification accuracy with a pre-existing detailed GIS wetland vegetation database. Though the accuracy varied greatly for different classes the algal communities were successfully identified which are the major sources of food for flamingo. The results from this study have practical implications for uses of spaceborne hyperspectral image data that are now becoming available. Practical limitations of using these satellite data for wetland vegetation mapping include inadequate spatial resolution, complexity of image processing procedures, and lack of stereo viewing.

Keywords: Algal community, NASA’s EO-1 Hyperion, salt-tolerant species, wetland vegetation mapping

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Authors: Victor Jeifets, Liliia Khadorich

Abstract:

The paper describes the OAS role in dispute resolution. The authors make an attempt to identify a general pattern of the OAS activities within the peaceful settlement of interstate conflicts, in the beginning of 21st century, as well as to analyze some features of Honduras–Belize, Nicaragua–Honduras, Honduras–El Salvador, Costa-Rica–Nicaragua, Colombia–Ecuador cases.

Keywords: OAS, peace maintenance, border dispute, dispute resolution, peaceful settlement

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