Search results for: image of Y series actors
5982 The Image as an Initial Element of the Cognitive Understanding of Words
Authors: S. Pesina, T. Solonchak
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An analysis of word semantics focusing on the invariance of advanced imagery in several pressing problems. Interest in the language of imagery is caused by the introduction, in the linguistics sphere, of a new paradigm, the center of which is the personality of the speaker (the subject of the language). Particularly noteworthy is the question of the place of the image when discussing the lexical, phraseological values and the relationship of imagery and metaphors. In part, the formation of a metaphor, as an interaction between two intellective entities, occurs at a cognitive level, and it is the category of the image, having cognitive roots, which aides in the correct interpretation of the results of this process on the lexical-semantic level.Keywords: image, metaphor, concept, creation of a metaphor, cognitive linguistics, erased image, vivid image
Procedia PDF Downloads 3615981 The Analogue of a Property of Pisot Numbers in Fields of Formal Power Series
Authors: Wiem Gadri
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This study delves into the intriguing properties of Pisot and Salem numbers within the framework of formal Laurent series over finite fields, a domain where these numbers’ spectral charac-teristics, Λm(β) and lm(β), have yet to be fully explored. Utilizing a methodological approach that combines algebraic number theory with the analysis of power series, we extend the foundational work of Erdos, Joo, and Komornik to this new setting. Our research uncovers bounds for lm(β), revealing how these depend on the degree of the minimal polynomial of β and thus offering a novel characterization of Pisot and Salem formal power series. The findings significantly contribute to our understanding of these numbers, highlighting their distribution and properties in the context of formal power series. This investigation not only bridges number theory with formal power series analysis but also sets the stage for further interdisciplinary research in these areas.Keywords: Pisot numbers, Salem numbers, formal power series, over a finite field
Procedia PDF Downloads 515980 Analyzing Middle Actors' Influence on Land Use Policy: A Case Study in Central Kalimantan, Indonesia
Authors: Kevin Soubly, Kaysara Khatun
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This study applies the existing Middle-Out Perspective (MOP) as a complementing analytical alternative to the customary dichotomous options of top-down vs. bottom-up strategies of international development and commons governance. It expands the framework by applying it to a new context of land management and environmental change, enabling fresh understandings of decision making around land use. Using a case study approach in Central Kalimantan, Indonesia among a village of indigenous Dayak, this study explores influences from both internal and external middle actors, utilizing qualitative empirical evidence and incorporating responses across 25 village households and 11 key stakeholders. Applying the factors of 'agency' and 'capacity' specific to the MOP, this study demonstrates middle actors’ unique capabilities and criticality to change due to their influence across various levels of decision-making. Study results indicate that middle actors play a large role, both passively and actively, both directly and indirectly, across various levels of decision-making, perception-shaping, and commons governance. In addition, the prominence of novel 'passive' middle actors, such as the internet, can provide communities themselves with a level of agency beyond that provided by other middle actors such as NGOs and palm oil industry entities – which often operate at the behest of the 'top' or out of self-interest. Further, the study posits that existing development and decision-making frameworks may misidentify the 'bottom' as the 'middle,' raising questions about traditional development and livelihood discourse, strategies, and support, from agricultural production to forest management. In conclusion, this study provides recommendations including that current policy preconceptions be reevaluated to engage middle actors in locally-adapted, integrative manners in order to improve governance and rural development efforts more broadly.Keywords: environmental management, governance, Indonesia, land use, middle actors, middle-out perspective
Procedia PDF Downloads 1155979 Nonstationarity Modeling of Economic and Financial Time Series
Authors: C. Slim
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Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.Keywords: stationarity, unit root tests, economic time series, ADF tests
Procedia PDF Downloads 4205978 Application of Change Detection Techniques in Monitoring Environmental Phenomena: A Review
Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari
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Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.Keywords: environmental phenomena, change detection, monitor, techniques
Procedia PDF Downloads 2745977 L1-Convergence of Modified Trigonometric Sums
Authors: Sandeep Kaur Chouhan, Jatinderdeep Kaur, S. S. Bhatia
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The existence of sine and cosine series as a Fourier series, their L1-convergence seems to be one of the difficult question in theory of convergence of trigonometric series in L1-metric norm. In the literature so far available, various authors have studied the L1-convergence of cosine and sine trigonometric series with special coefficients. In this paper, we present a modified cosine and sine sums and criterion for L1-convergence of these modified sums is obtained. Also, a necessary and sufficient condition for the L1-convergence of the cosine and sine series is deduced as corollaries.Keywords: conjugate Dirichlet kernel, Dirichlet kernel, L1-convergence, modified sums
Procedia PDF Downloads 3545976 Image Classification with Localization Using Convolutional Neural Networks
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
Procedia PDF Downloads 3055975 Detecting the Edge of Multiple Images in Parallel
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
Procedia PDF Downloads 4785974 Speeding-up Gray-Scale FIC by Moments
Authors: Eman A. Al-Hilo, Hawraa H. Al-Waelly
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In this work, fractal compression (FIC) technique is introduced based on using moment features to block indexing the zero-mean range-domain blocks. The moment features have been used to speed up the IFS-matching stage. Its moments ratio descriptor is used to filter the domain blocks and keep only the blocks that are suitable to be IFS matched with tested range block. The results of tests conducted on Lena picture and Cat picture (256 pixels, resolution 24 bits/pixel) image showed a minimum encoding time (0.89 sec for Lena image and 0.78 of Cat image) with appropriate PSNR (30.01dB for Lena image and 29.8 of Cat image). The reduction in ET is about 12% for Lena and 67% for Cat image.Keywords: fractal gray level image, fractal compression technique, iterated function system, moments feature, zero-mean range-domain block
Procedia PDF Downloads 4925973 Digital Image Forensics: Discovering the History of Digital Images
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
Procedia PDF Downloads 2475972 Eco-Politics of Infrastructure Development in and Around Protected Areas in Kenya: The Case of Nairobi National Park
Authors: Teresa Wanjiru Mbatia
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On 7th June 2011, the government Minister of Roads in Kenya announced the proposed construction of a major highway known as a southern bypass to run on the northern border of the Nairobi National Park. The following day on 8th June 2011, the chairperson of the Friends of Nairobi National Park (FONNAP) posted a protest statement on their website, with the heading, ‘Nairobi Park is Not a cake’ alerting its members and conservation groups, with the aim of getting support to the campaign against the government’s intention to hive off a section of the park for road construction. This was the first and earliest statement that led to a series of other events that culminated in conservationists and some other members of the public campaign against the government’s plan to hive off sections of the park to build road and railway infrastructure in or around the park. Together with other non-state actors, mostly non-governmental organisations in conservation/environment and tourism businesses, FoNNAP issued a series of other statements on social, print and electronic media to battle against road and railway construction. This paper examined the strategies, outcomes and interests of actors involved in opposing/proposing the development of transport infrastructure in and around the Nairobi National Park. Specifically, the objectives were to analyse the: (1) Arguments put forward by the eco-warriors to protest infrastructure development; (2) Background and interests of the eco-warriors; (3) Needs/interests and opinions of ordinary common citizens on transport infrastructural development, particularly in and around the urban nature reserve and (4) Final outcomes of the eco-politics surrounding infrastructure development in and around Nairobi National Park. The methodological approach used was environmental history and the social construction of nature. The study collected combined qualitative data using four main approaches, the grounded theory approach, narratives, case studies and a phenomenological approach. The information collected was analysed using critical discourse analysis. The major findings of the study were that under the guise of “public participation,” influential non-state actors have the capacity to perpetuate social-spatial inequalities in the form of curtailing the majority from accessing common public goods. A case in point in this study is how the efforts of powerful conservationists, environmentalists, and tourism businesspersons managed to stall the construction of much-needed road and railway infrastructure severally through litigations in lengthy environmental court processes involving injunctions and stop orders to the government bodies in charge. Moreover, powerful non-state actors were found to have formed informal and sometimes formal coalitions with politicians with selfish interests, which serves to deepen the exclusionary practices and the common good. The study concludes that mostly composed of certain types of elites (NGOs, business communities, politicians and privileged social-cultural groups), non-state actors have used participatory policies to advance their own interests at the expense of the majority whom they claim to represent. These practices are traced to the historically unjust social, political, and economic forces involved in the production of space in Nairobi.Keywords: eco-politics, exclusion, infrastructure, Nairobi national park, non-state actors, protests
Procedia PDF Downloads 1795971 Gray Level Image Encryption
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
Procedia PDF Downloads 3305970 A Comparative Case Study of Institutional Work in Public Sector Organizations: Creating Knowledge Management Practice
Authors: Dyah Adi Sriwahyuni
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Institutional work has become a prominent and contemporary institutional theory perspective in organization studies. A wealth of studies in organizations have explored actor activities in creating, maintaining, and disrupting institutions at the field level. However, the exploration of the work of actors in creating new management practices at the organizational level has been somewhat limited. The current institutional work literature mostly describes the work of actors at the field level and ignores organizational actors who work to realize management practices. Organizational actors here are defined as actors in organizations who work to institutionalize a particular management practice within the organizations. The extant literature has also generalized the types of management practices, which meant overlooking the unique characteristics of each management fashion as well as a management practice. To fill these gaps, this study aims to provide empirical evidence so as to contribute theoretically to institutional work through a comparative case study on organizational actors’ creation of knowledge management (KM) practice in two public sector organizations in Indonesia. KM is a contemporary management practice employed to manage individual and organizational knowledge in order to improve organizational performance. This practice presents a suitable practical setting with which to provide a rich understanding of the organizational actors’ institutional work and their connection with technology. Drawing on and extending the work of Perkmann and Spicer (2008), this study explores the forms of institutional work performed by organizational actors, including their motivation, skills, challenges, and opportunities. The primary data collection is semi-structured interviews with knowledgeable actors and document analysis for validity and triangulation. Following Eisenhardt's cross-case patterns, the researcher analyzed the collected data focusing on within-group similarities and intergroup differences. The researcher coded interview data using NVivo and used documents to corroborate the findings. The study’s findings add to the wealth of institutional theory literature in organization studies, particularly institutional work related to management practices. This study builds a theory about the work of organizational actors in creating knowledge management practices. Using the perspective of institutional work, research can show the roles of the various actors involved, their practices, and their relationship to technology (materiality), not only focusing on actors with a power which has been the theorizing of institutional entrepreneurship. The development of knowledge management practices in the Indonesian public sector is also a significant additional contribution, given that the current KM literature is dominated by conceptualizing the KM framework and the impact of KM on organizations. The public sector, which is the research setting, also provides important lessons on how actors in a highly institutionalized context are creating an institution, in this case, a knowledge management practice.Keywords: institutional work, knowledge management, case study, public sector organizations
Procedia PDF Downloads 1185969 Data Hiding in Gray Image Using ASCII Value and Scanning Technique
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
Procedia PDF Downloads 4145968 High-Capacity Image Steganography using Wavelet-based Fusion on Deep Convolutional Neural Networks
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
Procedia PDF Downloads 905967 Investigation on Performance of Change Point Algorithm in Time Series Dynamical Regimes and Effect of Data Characteristics
Authors: Farhad Asadi, Mohammad Javad Mollakazemi
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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm
Procedia PDF Downloads 4265966 Review of Friction Stir Welding of Dissimilar 5000 and 6000 Series Aluminum Alloy Plates
Authors: K. Subbaiah
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Friction stir welding is a solid state welding process. Friction stir welding process eliminates the defects found in fusion welding processes. It is environmentally friend process. 5000 and 6000 series aluminum alloys are widely used in the transportation industries. The Al-Mg-Mn (5000) and Al-Mg-Si (6000) alloys are preferably offer best combination of use in Marine construction. The medium strength and high corrosion resistant 5000 series alloys are the aluminum alloys, which are found maximum utility in the world. In this review, the tool pin profile, process parameters such as hardness, yield strength and tensile strength, and microstructural evolution of friction stir welding of Al-Mg alloys 5000 Series and 6000 series have been discussed.Keywords: 5000 series and 6000 series Al alloys, friction stir welding, tool pin profile, microstructure and properties
Procedia PDF Downloads 4655965 Image Segmentation Techniques: Review
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
Procedia PDF Downloads 965964 Improvement Image Summarization using Image Processing and Particle swarm optimization Algorithm
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
Procedia PDF Downloads 1335963 Massive Deployments of Insurgent Intelligence by Violent Non-state Actors (VNSAs) in the 21st Century and Threats to Global Security
Authors: Temitope Francis Abiodun
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The practice of intelligence is not limited to the machinery of a nation state alone, yet not much research or analysis has been directed towards the spy-crafts and tradecrafts engaged in by violent non-state actors (VNSAs) in the international community. The rise of 'private sector intelligence' in more recent years has only just begun to be interrogated by practitioners and academics. However, the use of intelligence by insurgents and other groups assembled to achieve varied forms of politico-military outcomes has often been overlooked. This paper examined the factors and conditions that gave rise to an increase in violent non-state actors (VNSAs), strategies aiding their deployment of insurgent intelligence, and as well the implications of their activities on global security. The failed state theory was adopted, while a descriptive research design served as the framework for the study. Data were collected from primary and secondary sources. The paper, however, revealed there were massive deployments of insurgent intelligence by violent non-state actors in contrast to a faulty pre-conception that insurgents were not as highly trained in deployment of intelligence as state actors, having assumed that the VNSAs lacked the sophistication to produce intelligence. However, the strategic objectives of insurgents (VNSAs) were revealed to depend on well-organized information gathering operations that feed into the tactical executions of their insurgency. The paper recommends, therefore, there is a need for adequate training on the part of security personnel in the states to be alive to their responsibilities; and there is also a need to ensure adequate border control and management to checkmate the influx of the various violent or deadly movements across global frontiers.Keywords: terrorism, non-violent state actors, private sector intelligence, security
Procedia PDF Downloads 1375962 Improved Super-Resolution Using Deep Denoising Convolutional Neural Network
Authors: Pawan Kumar Mishra, Ganesh Singh Bisht
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Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.Keywords: resolution, deep-learning, neural network, de-blurring
Procedia PDF Downloads 5175961 High Secure Data Hiding Using Cropping Image and Least Significant Bit Steganography
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
Procedia PDF Downloads 2695960 Image Processing on Geosynthetic Reinforced Layers to Evaluate Shear Strength and Variations of the Strain Profiles
Authors: S. K. Khosrowshahi, E. Güler
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This study investigates the reinforcement function of geosynthetics on the shear strength and strain profile of sand. Conducting a series of simple shear tests, the shearing behavior of the samples under static and cyclic loads was evaluated. Three different types of geosynthetics including geotextile and geonets were used as the reinforcement materials. An image processing analysis based on the optical flow method was performed to measure the lateral displacements and estimate the shear strains. It is shown that besides improving the shear strength, the geosynthetic reinforcement leads a remarkable reduction on the shear strains. The improved layer reduces the required thickness of the soil layer to resist against shear stresses. Consequently, the geosynthetic reinforcement can be considered as a proper approach for the sustainable designs, especially in the projects with huge amount of geotechnical applications like subgrade of the pavements, roadways, and railways.Keywords: image processing, soil reinforcement, geosynthetics, simple shear test, shear strain profile
Procedia PDF Downloads 2205959 Secure E-Pay System Using Steganography and Visual Cryptography
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
Procedia PDF Downloads 3305958 Noise Detection Algorithm for Skin Disease Image Identification
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 processKeywords: MSE, PSNR, entropy, Gaussian filter, DWT
Procedia PDF Downloads 2155957 Understanding Solid Waste Management in Face of Political Instability: Actors, Roles, and Challenges to Sustainable Development in Kinshasa
Authors: Longondjo Etambakonga Clement
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Local municipality responsible for solid waste management (SWM) in many developing countries is facing real challenge. This is even more critical in the country facing political instability. Few decades ago, it has emerged new urban governance including partnerships and involvement of formal and informal actors for an effective and sustainable solid waste management. This paper identifies SWM actors and analyzes their roles to sustainable development in Kinshasa. An attempt has been to examine the challenges facing the actors in managing effectively waste in the city. The study is based on the empirical data gathered in the years 2009 and 2014 in Kinshasa using expert interviews, observation and documentation. The findings indicate that solid waste in the city is poorly managed, activities not coordinated and fragmented, as consequence severe public health and environmental problems. Five group actors are involved in SWM in the city including government, private business, NGOs/CBOs/donors, household, scavengers, in which, scavengers are more visible in collection and recycling activities. The results suggest that recognition of informal collectors and recyclers (scavengers) and strengthening alliances among all SWM stakeholders can lead to greater effective SWM in the city. The key lessons learned include lack of city’s SWM culture over SWM, unwillingness to pay and lack of environmental consciences are the main obstructions to sustainable SWM, therefore there is a need for social capital approach to empower individual and group actors as to create capabilities for an sustainable SWM.Keywords: challenges, institutions, political instability, scavengers, solid waste management, sustainable development
Procedia PDF Downloads 3525956 An Object-Based Image Resizing Approach
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
Procedia PDF Downloads 4765955 Rough Neural Networks in Adapting Cellular Automata Rule for Reducing Image Noise
Authors: Yasser F. Hassan
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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.Keywords: rough sets, rough neural networks, cellular automata, image processing
Procedia PDF Downloads 4395954 Coefficients of Some Double Trigonometric Cosine and Sine Series
Authors: Jatinderdeep Kaur
Abstract:
In this paper, the results of Kano from one-dimensional cosine and sine series are extended to two-dimensional cosine and sine series. To extend these results, some classes of coefficient sequences such as the class of semi convexity and class R are extended from one dimension to two dimensions. Under these extended classes, I have checked the function f(x,y) is two dimensional Fourier Cosine and Sine series or equivalently it represents an integrable function. Further, some results are obtained which are the generalization of Moricz's results.Keywords: conjugate dirichlet kernel, conjugate fejer kernel, fourier series, semi-convexity
Procedia PDF Downloads 4395953 Closed Forms of Trigonometric Series Interms of Riemann’s ζ Function and Dirichlet η, λ, β Functions or the Hurwitz Zeta Function and Harmonic Numbers
Authors: Slobodan B. Tričković
Abstract:
We present the results concerned with trigonometric series that include sine and cosine functions with a parameter appearing in the denominator. We derive two types of closed-form formulas for trigonometric series. At first, for some integer values, as we know that Riemann’s ζ function and Dirichlet η, λ equal zero at negative even integers, whereas Dirichlet’s β function equals zero at negative odd integers, after a certain number of members, the rest of the series vanishes. Thus, a trigonometric series becomes a polynomial with coefficients involving Riemann’s ζ function and Dirichlet η, λ, β functions. On the other hand, in some cases, one cannot immediately replace the parameter with any positive integer because we shall encounter singularities. So it is necessary to take a limit, so in the process, we apply L’Hospital’s rule and, after a series of rearrangements, we bring a trigonometric series to a form suitable for the application of Choi-Srivastava’s theorem dealing with Hurwitz’s zeta function and Harmonic numbers. In this way, we express a trigonometric series as a polynomial over Hurwitz’s zeta function derivative.Keywords: Dirichlet eta lambda beta functions, Riemann's zeta function, Hurwitz zeta function, Harmonic numbers
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