World Academy of Science, Engineering and Technology
[Computer and Information Engineering]
Online ISSN : 1307-6892
86 Intelligent Audio Watermarking using Genetic Algorithm in DWT Domain
Authors: M. Ketcham, S. Vongpradhip
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In this paper, an innovative watermarking scheme for audio signal based on genetic algorithms (GA) in the discrete wavelet transforms is proposed. It is robust against watermarking attacks, which are commonly employed in literature. In addition, the watermarked image quality is also considered. We employ GA for the optimal localization and intensity of watermark. The watermark detection process can be performed without using the original audio signal. The experimental results demonstrate that watermark is inaudible and robust to many digital signal processing, such as cropping, low pass filter, additive noise.
Keywords: Intelligent Audio Watermarking, GeneticAlgorithm, DWT Domain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 205785 A New Approach for Flexible Document Categorization
Authors: Jebari Chaker, Ounelli Habib
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In this paper we propose a new approach for flexible document categorization according to the document type or genre instead of topic. Our approach implements two homogenous classifiers: contextual classifier and logical classifier. The contextual classifier is based on the document URL, whereas, the logical classifier use the logical structure of the document to perform the categorization. The final categorization is obtained by combining contextual and logical categorizations. In our approach, each document is assigned to all predefined categories with different membership degrees. Our experiments demonstrate that our approach is best than other genre categorization approaches.
Keywords: Categorization, combination, flexible, logicalstructure, genre, category, URL.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 148484 Applications of Cascade Correlation Neural Networks for Cipher System Identification
Authors: B. Chandra, P. Paul Varghese
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Crypto System Identification is one of the challenging tasks in Crypt analysis. The paper discusses the possibility of employing Neural Networks for identification of Cipher Systems from cipher texts. Cascade Correlation Neural Network and Back Propagation Network have been employed for identification of Cipher Systems. Very large collection of cipher texts were generated using a Block Cipher (Enhanced RC6) and a Stream Cipher (SEAL). Promising results were obtained in terms of accuracy using both the Neural Network models but it was observed that the Cascade Correlation Neural Network Model performed better compared to Back Propagation Network.
Keywords: Back Propagation Neural Networks, CascadeCorrelation Neural Network, Crypto systems, Block Cipher, StreamCipher.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 244583 Feature Preserving Nonlinear Diffusion for Ultrasonic Image Denoising and Edge Enhancement
Authors: Shujun Fu, Qiuqi Ruan, Wenqia Wang, Yu Li
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Utilizing echoic intension and distribution from different organs and local details of human body, ultrasonic image can catch important medical pathological changes, which unfortunately may be affected by ultrasonic speckle noise. A feature preserving ultrasonic image denoising and edge enhancement scheme is put forth, which includes two terms: anisotropic diffusion and edge enhancement, controlled by the optimum smoothing time. In this scheme, the anisotropic diffusion is governed by the local coordinate transformation and the first and the second order normal derivatives of the image, while the edge enhancement is done by the hyperbolic tangent function. Experiments on real ultrasonic images indicate effective preservation of edges, local details and ultrasonic echoic bright strips on denoising by our scheme.
Keywords: anisotropic diffusion, coordinate transformationdirectional derivatives, edge enhancement, hyperbolic tangentfunction, image denoising.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 181382 Feature Preserving Image Interpolation and Enhancement Using Adaptive Bidirectional Flow
Authors: Shujun Fu, Qiuqi Ruan, Wenqia Wang
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Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually to some extent the effects of blurred edges and jagged artifacts in the image. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to enhance edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (''jaggies'') along the tangent directions. In order to preserve image features such as edges, angles and textures, the nonlinear diffusion coefficients are locally adjusted according to the first and second order directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Keywords: anisotropic diffusion, bidirectional flow, directionalderivatives, edge enhancement, image interpolation, inverse flow, shock filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 149881 Automated Feature Points Management for Video Mosaic Construction
Authors: Jing Li, Quan Pan, Stan. Z. Li, Tao Yang
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A novel algorithm for construct a seamless video mosaic of the entire panorama continuously by automatically analyzing and managing feature points, including management of quantity and quality, from the sequence is presented. Since a video contains significant redundancy, so that not all consecutive video images are required to create a mosaic. Only some key images need to be selected. Meanwhile, feature-based methods for mosaicing rely on correction of feature points? correspondence deeply, and if the key images have large frame interval, the mosaic will often be interrupted by the scarcity of corresponding feature points. A unique character of the method is its ability to handle all the problems above in video mosaicing. Experiments have been performed under various conditions, the results show that our method could achieve fast and accurate video mosaic construction. Keywords?video mosaic, feature points management, homography estimation.
Keywords: Video mosaic, feature points management, homography estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 182380 Effect of Neighborhood Size on Negative Weights in Punctual Kriging Based Image Restoration
Authors: Asmatullah Chaudhry, Anwar M. Mirza
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We present a general comparison of punctual kriging based image restoration for different neighbourhood sizes. The formulation of the technique under consideration is based on punctual kriging and fuzzy concepts for image restoration in spatial domain. Three different neighbourhood windows are considered to estimate the semivariance at different lags for studying its effect in reduction of negative weights resulted in punctual kriging, consequently restoration of degraded images. Our results show that effect of neighbourhood size higher than 5x5 on reduction in negative weights is insignificant. In addition, image quality measures, such as structure similarity indices, peak signal to noise ratios and the new variogram based quality measures; show that 3x3 window size gives better performance as compared with larger window sizes.
Keywords: Image restoration, punctual kriging, semi-variance, structure similarity index, negative weights in punctual kriging.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 235879 Blur and Ringing Artifact Measurement in Image Compression using Wavelet Transform
Authors: Madhuri Khambete, Madhuri Joshi
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Quality evaluation of an image is an important task in image processing applications. In case of image compression, quality of decompressed image is also the criterion for evaluation of given coding scheme. In the process of compression -decompression various artifacts such as blocking artifacts, blur artifact, ringing or edge artifact are observed. However quantification of these artifacts is a difficult task. We propose here novel method to quantify blur and ringing artifact in an image.
Keywords: Blur, Compression, Objective Quality assessment, Ringing artifact.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 485378 Image Authenticity and Perceptual Optimization via Genetic Algorithm and a Dependence Neighborhood
Authors: Imran Usman, Asifullah Khan, Rafiullah Chamlawi, Abdul Majid
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Information hiding for authenticating and verifying the content integrity of the multimedia has been exploited extensively in the last decade. We propose the idea of using genetic algorithm and non-deterministic dependence by involving the un-watermarkable coefficients for digital image authentication. Genetic algorithm is used to intelligently select coefficients for watermarking in a DCT based image authentication scheme, which implicitly watermark all the un-watermarkable coefficients also, in order to thwart different attacks. Experimental results show that such intelligent selection results in improvement of imperceptibility of the watermarked image, and implicit watermarking of all the coefficients improves security against attacks such as cover-up, vector quantization and transplantation.
Keywords: Digital watermarking, fragile watermarking, geneticalgorithm, Image authentication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 152077 Probability Density Estimation Using Advanced Support Vector Machines and the Expectation Maximization Algorithm
Authors: Refaat M Mohamed, Ayman El-Baz, Aly A. Farag
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This paper presents a new approach for the prob-ability density function estimation using the Support Vector Ma-chines (SVM) and the Expectation Maximization (EM) algorithms.In the proposed approach, an advanced algorithm for the SVM den-sity estimation which incorporates the Mean Field theory in the learning process is used. Instead of using ad-hoc values for the para-meters of the kernel function which is used by the SVM algorithm,the proposed approach uses the EM algorithm for an automatic optimization of the kernel. Experimental evaluation using simulated data set shows encouraging results.
Keywords: Density Estimation, SVM, Learning Algorithms, Parameters Estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 250676 Simulation Tools for Fixed Point DSP Algorithms and Architectures
Authors: K. B. Cullen, G. C. M. Silvestre, N. J. Hurley
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This paper presents software tools that convert the C/Cµ floating point source code for a DSP algorithm into a fixedpoint simulation model that can be used to evaluate the numericalperformance of the algorithm on several different fixed pointplatforms including microprocessors, DSPs and FPGAs. The tools use a novel system for maintaining binary point informationso that the conversion from floating point to fixed point isautomated and the resulting fixed point algorithm achieves maximum possible precision. A configurable architecture is used during the simulation phase so that the algorithm can produce a bit-exact output for several different target devices.
Keywords: DSP devices, DSP algorithm, simulation model, software
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 255275 Quantitative Analysis of Weld Defect Images in Industrial Radiography Based Invariant Attributes
Authors: N. Nacereddine, M. Tridi, S. S. Belaïfa, M. Zelmat
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For the characterization of the weld defect region in the radiographic image, looking for features which are invariant regarding the geometrical transformations (rotation, translation and scaling) proves to be necessary because the same defect can be seen from several angles according to the orientation and the distance from the welded framework to the radiation source. Thus, panoply of geometrical attributes satisfying the above conditions is proposed and which result from the calculation of the geometrical parameters (surface, perimeter, etc.) on the one hand and the calculation of the different order moments, on the other hand. Because the large range in values of the raw features and taking into account other considerations imposed by some classifiers, the scaling of these values to lie between 0 and 1 is indispensable. The principal component analysis technique is used in order to reduce the number of the attribute variables in the aim to give better performance to the further defect classification.
Keywords: Geometric parameters, invariant attributes, principal component analysis, weld defect image.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 218174 Nuclear Medical Image Treatment System Based On FPGA in Real Time
Authors: B. Mahmoud, M.H. Bedoui, R. Raychev, H. Essabbah
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We present in this paper an acquisition and treatment system designed for semi-analog Gamma-camera. It consists of a nuclear medical Image Acquisition, Treatment and Display chain(IATD) ensuring the acquisition, the treatment of the signals(resulting from the Gamma-camera detection head) and the scintigraphic image construction in real time. This chain is composed by an analog treatment board and a digital treatment board. We describe the designed systems and the digital treatment algorithms in which we have improved the performance and the flexibility. The digital treatment algorithms are implemented in a specific reprogrammable circuit FPGA (Field Programmable Gate Array).interface for semi-analog cameras of Sopha Medical Vision(SMVi) by taking as example SOPHY DS7. The developed system consists of an Image Acquisition, Treatment and Display (IATD) ensuring the acquisition and the treatment of the signals resulting from the DH. The developed chain is formed by a treatment analog board and a digital treatment board designed around a DSP [2]. In this paper we have presented the architecture of a new version of our chain IATD in which the integration of the treatment algorithms is executed on an FPGA (Field Programmable Gate Array)
Keywords: Nuclear medical image, scintigraphic image, digitaltreatment, linearity, spectrometry, FPGA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 167673 Evaluating Performance of Quality-of-Service Routing in Large Networks
Authors: V. Narasimha Raghavan, M. Venkatesh, T. Peer Meera Labbai, Praveen Dwarakanath Prabhu
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The performance and complexity of QoS routing depends on the complex interaction between a large set of parameters. This paper investigated the scaling properties of source-directed link-state routing in large core networks. The simulation results show that the routing algorithm, network topology, and link cost function each have a significant impact on the probability of successfully routing new connections. The experiments confirm and extend the findings of other studies, and also lend new insight designing efficient quality-of-service routing policies in large networks.
Keywords: QoS, Link-State Routing, Dijkstra, Path Selection, Path Computation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 158172 Design and Implementation of a Hybrid Fuzzy Controller for a High-Performance Induction
Authors: M. Zerikat, S. Chekroun
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This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variations and external influences. Some fundamentals of the fuzzy logic control are preliminary illustrated. The developed control algorithm is robust, efficient and simple. It also assures precise trajectory tracking with the prescribed dynamics. Experimental results have shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the validity and the usefulness of the hybrid fuzzy controller in high-performance drives with parameter and load uncertainties. Satisfactory performance was observed for most reference tracks.
Keywords: Fuzzy controller, high-performance, inductionmotor, intelligent control, robustness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 217471 A Visual Cryptography and Statistics Based Method for Ownership Identification of Digital Images
Authors: Ching-Sheng Hsu, Young-Chang Hou
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In this paper, a novel copyright protection scheme for digital images based on Visual Cryptography and Statistics is proposed. In our scheme, the theories and properties of sampling distribution of means and visual cryptography are employed to achieve the requirements of robustness and security. Our method does not need to alter the original image and can identify the ownership without resorting to the original image. Besides, our method allows multiple watermarks to be registered for a single host image without causing any damage to other hidden watermarks. Moreover, it is also possible for our scheme to cast a larger watermark into a smaller host image. Finally, experimental results will show the robustness of our scheme against several common attacks.
Keywords: Copyright protection, digital watermarking, samplingdistribution, visual cryptography.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 188370 Generalized Morphological 3D Shape Decomposition Grayscale Interframe Interpolation Method
Authors: Dragos Nicolae VIZIREANU
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One of the main image representations in Mathematical Morphology is the 3D Shape Decomposition Representation, useful for Image Compression and Representation,and Pattern Recognition. The 3D Morphological Shape Decomposition representation can be generalized a number of times,to extend the scope of its algebraic characteristics as much as possible. With these generalizations, the Morphological Shape Decomposition 's role to serve as an efficient image decomposition tool is extended to grayscale images.This work follows the above line, and further develops it. Anew evolutionary branch is added to the 3D Morphological Shape Decomposition's development, by the introduction of a 3D Multi Structuring Element Morphological Shape Decomposition, which permits 3D Morphological Shape Decomposition of 3D binary images (grayscale images) into "multiparameter" families of elements. At the beginning, 3D Morphological Shape Decomposition representations are based only on "1 parameter" families of elements for image decomposition.This paper addresses the gray scale inter frame interpolation by means of mathematical morphology. The new interframe interpolation method is based on generalized morphological 3D Shape Decomposition. This article will present the theoretical background of the morphological interframe interpolation, deduce the new representation and show some application examples.Computer simulations could illustrate results.
Keywords: 3D shape decomposition representation, mathematical morphology, gray scale interframe interpolation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 174769 Weld Defect Detection in Industrial Radiography Based Digital Image Processing
Authors: N. Nacereddine, M. Zelmat, S. S. Belaïfa, M. Tridi
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Industrial radiography is a famous technique for the identification and evaluation of discontinuities, or defects, such as cracks, porosity and foreign inclusions found in welded joints. Although this technique has been well developed, improving both the inspection process and operating time, it does suffer from several drawbacks. The poor quality of radiographic images is due to the physical nature of radiography as well as small size of the defects and their poor orientation relatively to the size and thickness of the evaluated parts. Digital image processing techniques allow the interpretation of the image to be automated, avoiding the presence of human operators making the inspection system more reliable, reproducible and faster. This paper describes our attempt to develop and implement digital image processing algorithms for the purpose of automatic defect detection in radiographic images. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of global and local preprocessing and segmentation methods must be appropriated.
Keywords: Digital image processing, global and localapproaches, radiographic film, weld defect.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 407368 Semantic Spatial Objects Data Structure for Spatial Access Method
Authors: Kalum Priyanath Udagepola, Zuo Decheng, Wu Zhibo, Yang Xiaozong
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Modern spatial database management systems require a unique Spatial Access Method (SAM) in order solve complex spatial quires efficiently. In this case the spatial data structure takes a prominent place in the SAM. Inadequate data structure leads forming poor algorithmic choices and forging deficient understandings of algorithm behavior on the spatial database. A key step in developing a better semantic spatial object data structure is to quantify the performance effects of semantic and outlier detections that are not reflected in the previous tree structures (R-Tree and its variants). This paper explores a novel SSRO-Tree on SAM to the Topo-Semantic approach. The paper shows how to identify and handle the semantic spatial objects with outlier objects during page overflow/underflow, using gain/loss metrics. We introduce a new SSRO-Tree algorithm which facilitates the achievement of better performance in practice over algorithms that are superior in the R*-Tree and RO-Tree by considering selection queries.
Keywords: Outlier, semantic spatial object, spatial objects, SSRO-Tree, topo-semantic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 169567 A Neural Model of Object Naming
Authors: Alessio Plebe
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One astonishing capability of humans is to recognize thousands of different objects visually, and to learn the semantic association between those objects and words referring to them. This work is an attempt to build a computational model of such capacity,simulating the process by which infants learn how to recognize objects and words through exposure to visual stimuli and vocal sounds.One of the main fact shaping the brain of a newborn is that lights and colors come from entities of the world. Gradually the visual system learn which light sensations belong to same entities, despite large changes in appearance. This experience is common between humans and several other mammals, like non-human primates. But humans only can recognize a huge variety of objects, most manufactured by himself, and make use of sounds to identify and categorize them. The aim of this model is to reproduce these processes in a biologically plausible way, by reconstructing the essential hierarchy of cortical circuits on the visual and auditory neural paths.
Keywords: Auditory cortex, object recognition, self-organizingmaps
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 138566 Using Data Mining Techniques for Estimating Minimum, Maximum and Average Daily Temperature Values
Authors: S. Kotsiantis, A. Kostoulas, S. Lykoudis, A. Argiriou, K. Menagias
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Estimates of temperature values at a specific time of day, from daytime and daily profiles, are needed for a number of environmental, ecological, agricultural and technical applications, ranging from natural hazards assessments, crop growth forecasting to design of solar energy systems. The scope of this research is to investigate the efficiency of data mining techniques in estimating minimum, maximum and mean temperature values. For this reason, a number of experiments have been conducted with well-known regression algorithms using temperature data from the city of Patras in Greece. The performance of these algorithms has been evaluated using standard statistical indicators, such as Correlation Coefficient, Root Mean Squared Error, etc.
Keywords: regression algorithms, supervised machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 341865 An Augmented Automatic Choosing Control Designed by Extremizing a Combination of Hamiltonian and Lyapunov Functions for Nonlinear Systems with Constrained Input
Authors: Toshinori Nawata, Hitoshi Takata
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In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input. Constant terms which arise from section wise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics.Parameters included in the control are suboptimally selectedby extremizing a combination of Hamiltonian and Lyapunov functions with the aid of the genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.
Keywords: Augmented Automatic Choosing Control, NonlinearControl, Genetic Algorithm, Hamiltonian, Lyapunovfunction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 144164 Encryption Efficiency Analysis and Security Evaluation of RC6 Block Cipher for Digital Images
Authors: Hossam El-din H. Ahmed, Hamdy M. Kalash, Osama S. Farag Allah
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This paper investigates the encryption efficiency of RC6 block cipher application to digital images, providing a new mathematical measure for encryption efficiency, which we will call the encryption quality instead of visual inspection, The encryption quality of RC6 block cipher is investigated among its several design parameters such as word size, number of rounds, and secret key length and the optimal choices for the best values of such design parameters are given. Also, the security analysis of RC6 block cipher for digital images is investigated from strict cryptographic viewpoint. The security estimations of RC6 block cipher for digital images against brute-force, statistical, and differential attacks are explored. Experiments are made to test the security of RC6 block cipher for digital images against all aforementioned types of attacks. Experiments and results verify and prove that RC6 block cipher is highly secure for real-time image encryption from cryptographic viewpoint. Thorough experimental tests are carried out with detailed analysis, demonstrating the high security of RC6 block cipher algorithm. So, RC6 block cipher can be considered to be a real-time secure symmetric encryption for digital images.
Keywords: Block cipher, Image encryption, Encryption quality, and Security analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 242563 An Agent-Based Approach to Vehicle Routing Problem
Authors: Dariusz Barbucha, Piotr Jedrzejowicz
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The paper proposes and validates a new method of solving instances of the vehicle routing problem (VRP). The approach is based on a multiple agent system paradigm. The paper contains the VRP formulation, an overview of the multiple agent environment used and a description of the proposed implementation. The approach is validated experimentally. The experiment plan and the discussion of experiment results follow.
Keywords: multi-agent systems, population-based methods, vehiclerouting problem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 224562 Complex-Valued Neural Network in Image Recognition: A Study on the Effectiveness of Radial Basis Function
Authors: Anupama Pande, Vishik Goel
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A complex valued neural network is a neural network, which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in image and vision processing. In Neural networks, radial basis functions are often used for interpolation in multidimensional space. A Radial Basis function is a function, which has built into it a distance criterion with respect to a centre. Radial basis functions have often been applied in the area of neural networks where they may be used as a replacement for the sigmoid hidden layer transfer characteristic in multi-layer perceptron. This paper aims to present exhaustive results of using RBF units in a complex-valued neural network model that uses the back-propagation algorithm (called 'Complex-BP') for learning. Our experiments results demonstrate the effectiveness of a Radial basis function in a complex valued neural network in image recognition over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error on a neural network model with RBF units. Some inherent properties of this complex back propagation algorithm are also studied and discussed.
Keywords: Complex valued neural network, Radial BasisFunction, Image recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 241161 Scene Adaptive Shadow Detection Algorithm
Authors: Mohammed Ibrahim M, Anupama R.
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Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.
Keywords: homogeneity, penumbra, projection histogram, shadow correction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 190360 Towards an Extended SQLf: Bipolar Query Language with Preferences
Authors: L. Ludovic, R. Daniel, S-E Tbahriti
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Database management systems that integrate user preferences promise better solution for personalization, greater flexibility and higher quality of query responses. This paper presents a tentative work that studies and investigates approaches to express user preferences in queries. We sketch an extend capabilities of SQLf language that uses the fuzzy set theory in order to define the user preferences. For that, two essential points are considered: the first concerns the expression of user preferences in SQLf by so-called fuzzy commensurable predicates set. The second concerns the bipolar way in which these user preferences are expressed on mandatory and/or optional preferences.
Keywords: Flexible query language, relational database, userpreference.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 101359 Improving Cache Memory Utilization
Authors: Sami I. Serhan, Hamed M. Abdel-Haq
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In this paper, an efficient technique is proposed to manage the cache memory. The proposed technique introduces some modifications on the well-known set associative mapping technique. This modification requires a little alteration in the structure of the cache memory and on the way by which it can be referenced. The proposed alteration leads to increase the set size virtually and consequently to improve the performance and the utilization of the cache memory. The current mapping techniques have accomplished good results. In fact, there are still different cases in which cache memory lines are left empty and not used, whereas two or more processes overwrite the lines of each other, instead of using those empty lines. The proposed algorithm aims at finding an efficient way to deal with such problem.
Keywords: Modified Set Associative Mapping, Locality of Reference, Miss Ratio, Hit Ratio, Cache Memory, Clustered Behavior, Index Address, Tag Field, Status Field, and Complement of Index Address.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 192758 Edge-end Pixel Extraction for Edge-based Image Segmentation
Authors: Mahinda P. Pathegama, Özdemir Göl
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Extraction of edge-end-pixels is an important step for the edge linking process to achieve edge-based image segmentation. This paper presents an algorithm to extract edge-end pixels together with their directional sensitivities as an augmentation to the currently available mathematical models. The algorithm is implemented in the Java environment because of its inherent compatibility with web interfaces since its main use is envisaged to be for remote image analysis on a virtual instrumentation platform.
Keywords: edge-end pixels, image processing, imagesegmentation, pixel extraction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 215457 The Socio-Technical Indicator Model: Socially-Sensitive CMC Technology, with an Implementation of Representative Moderation
Authors: Zach-Amaury Boufoy-Bastick, Lenandlar Singh
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Computer-mediated communication technologies which provide for virtual communities have typically evolved in a cross-dichotomous manner, such that technical constructs of the technology have evolved independently from the social environment of the community. The present paper analyses some limitations of current implementations of computer-mediated communication technology that are implied by such a dichotomy, and discusses their inhibiting effects on possible developments of virtual communities. A Socio-Technical Indicator Model is introduced that utilizes integrated feedback to describe, simulate and operationalise increasing representativeness within a variety of structurally and parametrically diverse systems. In illustration, applications of the model are briefly described for financial markets and for eco-systems. A detailed application is then provided to resolve the aforementioned technical limitations of moderation on the evolution of virtual communities. The application parameterises virtual communities to function as self-transforming social-technical systems which are sensitive to emergent and shifting community values as products of on-going communications within the collective.
Keywords: Virtual community, e-democracy, feedback systems, moderation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1570