Search results for: particle image velocimetry

Authors: Ali A. Ukasha, Majdi F. Elbireki, Mohammad F. Abdullah

Abstract:

Data security needed in data transmission, storage, and communication to ensure the security. This paper is divided into two parts. This work interests with the color image which is decomposed into red, green and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using the key image that has same original size and are generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours from color images recovery can be obtained with accepted level of distortion using single step parallel contour extraction (SSPCE) method. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Color images and completely reconstructed without any distortion. Also shown that the analyzed algorithm has extremely large security against some attacks like salt and pepper and Jpeg compression. Its proof that the color images can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression and salt and peppers attacks, bitplanes decomposition, Arnold transform, color image, wavelet transform, lossless image encryption

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Authors: Alina Trifan, António J. R. Neves

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Although most digital cameras acquire images in a raw format, based on a Color Filter Array that arranges RGB color filters on a square grid of photosensors, most image compression techniques do not use the raw data; instead, they use the rgb result of an interpolation algorithm of the raw data. This approach is inefficient and by performing a lossless compression of the raw data, followed by pixel interpolation, digital cameras could be more power efficient and provide images with increased resolution given that the interpolation step could be shifted to an external processing unit. In this paper, we conduct a survey on the use of lossless compression algorithms with raw Bayer images. Moreover, in order to reduce the effect of the transition between colors that increase the entropy of the raw Bayer image, we split the image into three new images corresponding to each channel (red, green and blue) and we study the same compression algorithms applied to each one individually. This simple pre-processing stage allows an improvement of more than 15% in predictive based methods.

Keywords: bayer image, CFA, lossless compression, image coding standards

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Authors: Yung Gi Wu

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With the growing of computer and network, digital data can be spread to anywhere in the world quickly. In addition, digital data can also be copied or tampered easily so that the security issue becomes an important topic in the protection of digital data. Digital watermark is a method to protect the ownership of digital data. Embedding the watermark will influence the quality certainly. In this paper, Vector Quantization (VQ) is used to embed the watermark into the image to fulfill the goal of data hiding. This kind of watermarking is invisible which means that the users will not conscious the existing of embedded watermark even though the embedded image has tiny difference compared to the original image. Meanwhile, VQ needs a lot of computation burden so that we adopt a fast VQ encoding scheme by partial distortion searching (PDS) and mean approximation scheme to speed up the data hiding process. The watermarks we hide to the image could be gray, bi-level and color images. Texts are also can be regarded as watermark to embed. In order to test the robustness of the system, we adopt Photoshop to fulfill sharpen, cropping and altering to check if the extracted watermark is still recognizable. Experimental results demonstrate that the proposed system can resist the above three kinds of tampering in general cases.

Keywords: data hiding, vector quantization, watermark, color image

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Authors: In-Geun Lim, Sung-Woong Ra

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As high resolution satellite images can be used, lots of studies are carried out for exploiting these images in various fields. This paper proposes the method based on mathematical morphology for extracting the ‘horse's hoof shaped object’. This proposed method can make an automatic object detection system to track the meaningful object in a large satellite image rapidly. Mathematical morphology process can apply in binary image, so this method is very simple. Therefore this method can easily extract the ‘horse's hoof shaped object’ from any images which have indistinct edges of the tracking object and have different image qualities depending on filming location, filming time, and filming environment. Using the proposed method by which ‘horse's hoof shaped object’ can be rapidly extracted, the performance of the automatic object detection system can be improved dramatically.

Keywords: facility detection, satellite image, object, mathematical morphology

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Authors: B. Ramesh Naik, T. Venugopal

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This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

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Authors: Abdelraheem M. Aly, Minh Tuan Nguyen, Sang-Wook Lee

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The incompressible smoothed particle hydrodynamics (ISPH) is used to simulate impact free surface flows. In the ISPH, pressure is evaluated by solving pressure Poisson equation using a semi-implicit algorithm based on the projection method. The current ISPH method is applied to simulate dam break flow over an inclined plane with different inclination angles. The effects of inclination angle in the velocity of wave front and pressure distribution is discussed. The impact of circular cylinder over water in tank has also been simulated using ISPH method. The computed pressures on the solid boundaries is studied and compared with the experimental results.

Keywords: incompressible smoothed particle hydrodynamics, free surface flow, inclined plane, water entry impact

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Authors: Kapse Swapnil, K. Shankar

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Aiming at optimizing the weight and deflection of cantilever beam subjected to maximum stress and maximum deflection, Multi-objective Particle Swarm Optimization (MOPSO) with Utopia Point based local search is implemented. Utopia point is used to govern the search towards the Pareto Optimal set. The elite candidates obtained during the iterations are stored in an archive according to non-dominated sorting and also the archive is truncated based on least crowding distance. Local search is also performed on elite candidates and the most diverse particle is selected as the global best. This method is implemented on standard test functions and it is observed that the improved algorithm gives better convergence and diversity as compared to NSGA-II in fewer iterations. Implementation on practical structural problem shows that in 5 to 6 iterations, the improved algorithm converges with better diversity as evident by the improvement of cantilever beam on an average of 0.78% and 9.28% in the weight and deflection respectively compared to NSGA-II.

Keywords: Utopia point, multi-objective particle swarm optimization, local search, cantilever beam

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Authors: G. R. Navaneesh, E. Nagarajan, C. H. Rajam Raju

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Nowadays the multimedia data are used to store some secure information. All previous methods allocate a space in image for data embedding purpose after encryption. In this paper, we propose a novel method by reserving space in image with a boundary surrounded before encryption with a traditional RDH algorithm, which makes it easy for the data hider to reversibly embed data in the encrypted images. The proposed method can achieve real time performance, that is, data extraction and image recovery are free of any error. A secure transmission process is also discussed in this paper, which improves the efficiency by ten times compared to other processes as discussed.

Keywords: secure communication, reserving room before encryption, least significant bits, image encryption, reversible data hiding

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Authors: Adil Al-Rammahi

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Image or document encryption is needed through e- government data base. Really in this paper we introduce two matrices images, one is the public, and the second is the secret (original). The analyses of each matrix is achieved using the transformation of singular values decomposition. So each matrix is transformed or analyzed to three matrices say row orthogonal basis, column orthogonal basis, and spectral diagonal basis. Product of the two row basis is calculated. Similarly the product of the two column basis is achieved. Finally we transform or save the files of public, row product and column product. In decryption stage, the original image is deduced by mutual method of the three public files.

Keywords: image cryptography, singular values decomposition

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Authors: R. Bouhennache, T. Bouden, A. A. Taleb, A. Chaddad

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In this paper we propose a method to map the urban areas. The method uses an arithmetic calculation processed from the land features indexes and Tasseled cap transformation TC of multi spectral Thematic Mapper Landsat TM image. For this purpose the derived indexes image from the original image such SAVI the soil adjusted vegetation index, UI the urban Index, and EBBI the enhanced built up and bareness index were staked to form a new image and the bands were uncorrelated, also the Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) supervised classification approaches were first applied on the new image TM data using the reference spectra of the spectral library and subsequently the four urban, vegetation, water and soil land cover categories were extracted with their accuracy assessment.The urban features were represented using a logic calculation applied to the brightness, UI-SAVI, NDBI-greenness and EBBI- brightness data sets. The study applied to Blida and mentioned that the urban features can be mapped with an accuracy ranging from 92 % to 95%.

Keywords: EBBI, SAVI, Tasseled Cap Transformation, UI

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Authors: Hazem Munawer Al-Otum

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In this work, an efficient watermarking technique is proposed and can be used for detecting intentional attacks in RGB color images. The proposed technique can be implemented for image authentication and exhibits high robustness against unintentional common image processing attacks. It deploys two measures to discern between intentional and unintentional attacks based on using a quantization-based technique in a modified 2D multi-pyramidal DWT transform. Simulations have shown high accuracy in detecting intentionally attacked regions while exhibiting high robustness under moderate to severe common image processing attacks.

Keywords: image authentication, copyright protection, semi-fragile watermarking, tamper detection

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Authors: Houda Abadlia, Nadia Smairi, Khaled Ghedira

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Multiobjective Particle Swarm Optimization (MOPSO) has shown an effective performance for solving test functions and real-world optimization problems. However, this method has a premature convergence problem, which may lead to lack of diversity. In order to improve its performance, this paper presents a hybrid approach which embedded the MOPSO into the island model and integrated a local search technique, Variable Neighborhood Search, to enhance the diversity into the swarm. Experiments on two series of test functions have shown the effectiveness of the proposed approach. A comparison with other evolutionary algorithms shows that the proposed approach presented a good performance in solving multiobjective optimization problems.

Keywords: particle swarm optimization, migration, variable neighborhood search, multiobjective optimization

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Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: Hossam M. Moftah, Aboul Ella Hassanien

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In the recent years the importance of automatic traffic control has increased due to the traffic jams problem especially in big cities for signal control and efficient traffic management. Traffic counting as a kind of traffic control is important to know the road traffic density in real time. This paper presents a fast and robust traffic counting system using different image processing techniques. The proposed system is composed of the following four fundamental building phases: image acquisition, pre-processing, object detection, and finally counting the connected objects. The object detection phase is comprised of the following five steps: subtracting the background, converting the image to binary, closing gaps and connecting nearby blobs, image smoothing to remove noises and very small objects, and detecting the connected objects. Experimental results show the great success of the proposed approach.

Keywords: traffic counting, traffic management, image processing, object detection, computer vision

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Authors: Harsh Vikram Singh, Ankur Rai, Anand Mohan

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In this paper, we propose secure and robust data hiding algorithm based on DCT by Arnold transform and chaotic sequence. The watermark image is scrambled by Arnold cat map to increases its security and then the chaotic map is used for watermark signal spread in middle band of DCT coefficients of the cover image The chaotic map can be used as pseudo-random generator for digital data hiding, to increase security and robustness .Performance evaluation for robustness and imperceptibility of proposed algorithm has been made using bit error rate (BER), normalized correlation (NC), and peak signal to noise ratio (PSNR) value for different watermark and cover images such as Lena, Girl, Tank images and gain factor .We use a binary logo image and text image as watermark. The experimental results demonstrate that the proposed algorithm achieves higher security and robustness against JPEG compression as well as other attacks such as addition of noise, low pass filtering and cropping attacks compared to other existing algorithm using DCT coefficients. Moreover, to recover watermarks in proposed algorithm, there is no need to original cover image.

Keywords: data hiding, watermarking, DCT, chaotic sequence, arnold transforms

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Authors: Ridvan Yamanoglu

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In the current study, titanium based composites reinforced by hard nickel alloy particles were produced. Powder metallurgical hot pressing technique was used for the fabrication of composite materials. The composites containing different ratio of hard nickel particles were sintered at 900 oC for 15 and 30 minutes under 50 MPa pressure. All titanium based composites were obtained under a vacuum atmosphere of 10-4 mbar to prevent of oxidation of titanium due to its high reactivity to oxygen. The microstructural characterization of the composite samples was carried out by optical and scanning electron microscopy. The mechanical properties of the samples were determined by means of hardness and wear tests. The results showed that when the nickel particle content increased the mechanical properties of the composites enhanced. The results are discussed in detail and optimum nickel particle content were determined.

Keywords: titanium, composite, nickel, hot pressing

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Authors: Krzysztof Malczewski

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Magnetic Resonance Imaging (MRI) reconstruction algorithm using compressed sensing is presented in this paper. It is exhibited that the offered approach improves MR images spatial resolution in circumstances when highly undersampled k-space trajectories are applied. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were conventionally assumed necessary. Magnetic Resonance Imaging (MRI) is a fundamental medical imaging method struggles with an inherently slow data acquisition process. The use of CS to MRI has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the objective is to combine super-resolution image enhancement algorithm with CS framework benefits to achieve high resolution MR output image. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity. The presented algorithm considers the cardiac and respiratory movements.

Keywords: super-resolution, MRI, compressed sensing, sparse-sense, image enhancement

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Authors: R. Kiruthika, A. Kannan

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Steganography is the problem of hiding secret messages in 'innocent – looking' public communication so that the presence of the secret message cannot be detected. This paper introduces a steganographic security in terms of computational in-distinguishability from a channel of probability distributions on cover messages. This method first splits the cover image into two separate blocks using Douglas – Peucker algorithm. The text message and the image will be hided in the Least Significant Bit (LSB) of the cover image.

Keywords: steganography, lsb, embedding, Douglas-Peucker algorithm

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Authors: Bin Liu, Weijie Liu, Bin Sun, Yihui Luo

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In order to solve the problem of lower spatial resolution and block effect in the fusion method based on separable wavelet transform in the resulting fusion image, a new sampling mode based on multi-resolution analysis of two-channel non separable wavelet transform, whose dilation matrix is [1,1;1,-1], is presented and a multispectral image fusion method based on this kind of sampling mode is proposed. Filter banks related to this kind of wavelet are constructed, and multiresolution decomposition of the intensity of the MS and panchromatic image are performed in the sampled mode using the constructed filter bank. The low- and high-frequency coefficients are fused by different fusion rules. The experiment results show that this method has good visual effect. The fusion performance has been noted to outperform the IHS fusion method, as well as, the fusion methods based on DWT, IHS-DWT, IHS-Contourlet transform, and IHS-Curvelet transform in preserving both spectral quality and high spatial resolution information. Furthermore, when compared with the fusion method based on nonsubsampled two-channel non separable wavelet, the proposed method has been observed to have higher spatial resolution and good global spectral information.

Keywords: image fusion, two-channel sampled nonseparable wavelets, multispectral image, panchromatic image

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Authors: Ashis Pradhan, Mohan P. Pradhan

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Pattern Matching is useful for recognizing character in a digital image. OCR is one such technique which reads character from a digital image and recognizes them. Line segmentation is initially used for identifying character in an image and later refined by morphological operations like binarization, erosion, thinning, etc. The work discusses a recognition technique that defines a set of morphological operators based on its orientation in a character. These operators are further categorized into groups having similar shape but different orientation for efficient utilization of memory. Finally the characters are recognized in accordance with the occurrence of frequency in hierarchy of significant pattern of those morphological operators and by comparing them with the existing database of each character.

Keywords: binary image, morphological patterns, frequency count, priority, reduction data set and recognition

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Authors: Khaled M. Nabil

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This paper introduces the Nested Vortexes conception of the universe structure and interprets all the physical phenomena according this conception. The paper first reviews recent physics theories, either in microscopic scale or macroscopic scale, to collect evidence that the space is not empty. But, these theories describe the property of the space medium without determining its structure. Determining the structure of space medium is essential to understand the mechanism that leads to its properties. Without determining the space medium structure, many phenomena; such as electric and magnetic fields, gravity, or wave-particle duality remain uninterpreted. Thus, this paper introduces a conception about the structure of the universe. It assumes that the universe is a medium of ultra-tiny homogeneous particles which are still undiscovered. Like any medium with certain movements, possibly because of a great asymmetric explosion, vortexes have occurred. A vortex condenses the ultra-tiny particles in its center forming a bigger particle, the bigger particles, in turn, could be trapped in a bigger vortex and condense in its center forming a much bigger particle and so on. This conception describes galaxies, stars, protons as particles at different levels. Existing of the particle’s vortexes make the consistency of the speed of light postulate is not true. This conception shows that the vortex motion dynamic agrees with the motion of all the universe particles at any level. An experiment has been carried out to detect the orbiting effect of aggregated vortexes of aligned atoms of a permanent magnet. Based on the described particle’s structure, the gravity force of a particle and attraction between particles as well as charge, electric and magnetic fields and quantum mechanics characteristics are interpreted. All augmented physics phenomena are solved.

Keywords: astrophysics, cosmology, particles’ structure model, particles’ forces

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Authors: Majid Forghani, Michael Khachay

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In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition

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Authors: Awad Mohamed Elkhadir, Rajab M. Ben Yousef

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Background/Aim: Radiological technologists are medical professionals who perform diagnostic imaging tests such as X-rays, magnetic resonance imaging (MRI) scans, and computer tomography (CT) scans. Despite the recognition of image interpretation by British radiologists, it is still considered a problem in the Arab world. This study evaluates the perceptions of radiologists in the Middle East concerning the plain image interpretation of adults by radiologic technologist specialists. Methods: This is a cross-sectional study that follows a quantitative approach. A close-ended questionnaire was distributed among 103 participants who were radiologists by profession from various hospitals in Saudi Arabia and Sudan. The gathered data was then analyzed through Statistical Package for Social Sciences (SPSS). Results: The results showed that 29% recognized the Radiologic Technologist Specialist (RTS) role of writing image reports, while 61% did not. A total of 38% of participants believed that RTS image interpretation would help diagnose unreported radiographs. 47% of the sample responded that the workload and stress on radiologists would reduce by allowing reporting for RTS, while 37% did not. Lastly, 43% believe that image interpretation by RTS can be introduced into the Middle East in the future. Conclusion: The study's findings reveal that the combination of image reporting and radiography improves the care of the patients. The study's outcomes also show that the burden of the medical practitioners reduces due to image reporting of the radiographers. Further researches need to be conducted in the Arab World to obtain and measure the associated factors of the desired criteria.

Keywords: Arab world, image interpretation, radiographer, radiologist, Saudi Arabia, Sudan

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Authors: Baljit Singh Khehra, Jagreeti Kaur

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In this paper, steganographic strategy is used to hide the text file inside an image. To increase the storage limit, predictive coding is utilized to implant information. In the proposed plan, one can exchange secure information by means of predictive coding methodology. The predictive coding produces high stego-image. The pixels are utilized to insert mystery information in it. The proposed information concealing plan is powerful as contrasted with the existing methodologies. By applying this strategy, a provision helps clients to productively conceal the information. Entropy, standard deviation, mean square error and peak signal noise ratio are the parameters used to evaluate the proposed methodology. The results of proposed approach are quite promising.

Keywords: cryptography, steganography, reversible image, predictive coding

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Authors: Awad Elkhadir, Rajab M. Ben Yousef

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Introduction: The production of high-quality medical images by radiology technologists is useful in diagnosing and treating various injuries and diseases. However, the factors affecting the role of radiology technologists in image interpretation in Sudan have not been investigated widely. Methods: Cross-sectional study has been employed by recruiting ten radiology college deans in Sudan. The questionnaire was distributed online, and obtained data were analyzed using Microsoft Excel and IBM-SPSS version 16.0 to generate descriptive statistics. Results: The study results have shown that half of the deans were doubtful about the readiness of Sudan to implement the role of radiology technologist specialist in image interpretation. The majority of them (60%) believed that this issue had been most strongly pushed by researchers over the past decade. The factors affecting the implementation of the radiology technologist specialist role in image interpretation included; education/training (100%), recognition (30%), technical issues (30%), people-related issues (20%), management changes (30%), government role (30%), costs (10%), and timings (20%). Conclusion: The study concluded that there is a need for a change in image interpretation by radiology technologists in Sudan.

Keywords: development, image interpretation, implementation, radiology technologist specialist, Sudan

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Authors: Hui Zhu, Yuan Wang, Shibo Kuang, Aibing Yu

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The inertial difference induced by the microfluidics inside a curved micro-channel has great potential to provide a fast, inexpensive, and portable solution to the separation of micro- and sub-micro particles in many applications such as aerosol collections, airborne bacteria and virus detections, as well as particle sortation. In this work, the separation behaviors of different sized particles inside a reported curved micro-channel have been studied by a combined approach of computational fluid dynamics for gas and discrete element model for particles (CFD-DEM). The micro-channel is operated by controlling the gas flow rates at all of its branches respectively used to load particles, introduce gas streams, collect particles of various sizes. The validity of the model has been examined by comparing by the calculated separation efficiency of different sized particles against the measurement. On this basis, the separation mechanisms of the inertial microfluidic separator are elucidated in terms of the interactions between particles, between particle and fluid, and between particle and wall. The model is then used to study the effect of feed solids concentration on the separation accuracy and efficiency. The results obtained from the present study demonstrate that the CFD-DEM approach can provide a convenient way to study the particle separation behaviors in micro-channels of various types.

Keywords: CFD-DEM, inertial effect, microchannel, separation

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Authors: Peter U. Eze, P. Udaya, Robin J. Evans

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Data hiding can be achieved by Steganography or invisible digital watermarking. For digital watermarking, both accurate retrieval of the embedded watermark and the integrity of the cover image are important. Medical image security in Teleradiology is one of the applications where the embedded patient record needs to be extracted with accuracy as well as the medical image integrity verified. In this research paper, the Constant Correlation Spread Spectrum digital watermarking for medical image tamper detection and accurate embedded watermark retrieval is introduced. In the proposed method, a watermark bit from a patient record is spread in a medical image sub-block such that the correlation of all watermarked sub-blocks with a spreading code, W, would have a constant value, p. The constant correlation p, spreading code, W and the size of the sub-blocks constitute the secret key. Tamper detection is achieved by flagging any sub-block whose correlation value deviates by more than a small value, ℇ, from p. The major features of our new scheme include: (1) Improving watermark detection accuracy for high-pixel depth medical images by reducing the Bit Error Rate (BER) to Zero and (2) block-level tamper detection in a single computational process with simultaneous watermark detection, thereby increasing utility with the same computational cost.

Keywords: Constant Correlation, Medical Image, Spread Spectrum, Tamper Detection, Watermarking

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Authors: Bum-Soo Kim, Jin-Uk Kim

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In this paper, we design and implement a partial denoising boundary image matching system using indexing techniques. Converting boundary images to time-series makes it feasible to perform fast search using indexes even on a very large image database. Thus, using this converting method we develop a client-server system based on the previous partial denoising research in the GUI (graphical user interface) environment. The client first converts a query image given by a user to a time-series and sends denoising parameters and the tolerance with this time-series to the server. The server identifies similar images from the index by evaluating a range query, which is constructed using inputs given from the client, and sends the resulting images to the client. Experimental results show that our system provides much intuitive and accurate matching result.

Keywords: boundary image matching, indexing, partial denoising, time-series matching

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Lana Dalawr Jalal

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This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles (UAVs) in complex three-dimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively.

Keywords: obstacle avoidance, particle swarm optimization, three-dimensional path planning unmanned aerial vehicles

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