Search results for: subspace rotation algorithm
3773 Parameter Estimation of Induction Motors by PSO Algorithm
Authors: A. Mohammadi, S. Asghari, M. Aien, M. Rashidinejad
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After emergent of alternative current networks and their popularity, asynchronous motors became more widespread than other kinds of industrial motors. In order to control and run these motors efficiently, an accurate estimation of motor parameters is needed. There are different methods to obtain these parameters such as rotor locked test, no load test, DC test, analytical methods, and so on. The most common drawback of these methods is their inaccuracy in estimation of some motor parameters. In order to remove this concern, a novel method for parameter estimation of induction motors using particle swarm optimization (PSO) algorithm is proposed. In the proposed method, transient state of motor is used for parameter estimation. Comparison of the simulation results purtuined to the PSO algorithm with other available methods justifies the effectiveness of the proposed method.Keywords: induction motor, motor parameter estimation, PSO algorithm, analytical method
Procedia PDF Downloads 6333772 Dual Band Antenna Design with Compact Radiator for 2.5/5.2/5.8 Ghz Wlan Application Using Genetic Algorithm
Authors: Ramnath Narhete, Saket Pandey, Puran Gour
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This paper presents of dual-band planner antenna with a compact radiator for 2.4/5.2/5.8 proposed by optimizing its resonant frequency, Bandwidth of operation and radiation frequency using the genetic algorithm. The antenna consists L-shaped and E-shaped radiating element to generate two resonant modes for dual band operation. The above techniques have been successfully used in many applications. Dual band antenna with the compact radiator for 2.4/5.2/5.8 GHz WLAN application design and radiator size only width 8mm and a length is 11.3 mm. The antenna can we used for various application in the field of communication. Genetic algorithm will be used to design the antenna and impedance matching network.Keywords: genetic algorithm, dual-band E, dual-band L, WLAN, compact radiator
Procedia PDF Downloads 5793771 Mutual Information Based Image Registration of Satellite Images Using PSO-GA Hybrid Algorithm
Authors: Dipti Patra, Guguloth Uma, Smita Pradhan
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Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information
Procedia PDF Downloads 4083770 Intrusion Detection Based on Graph Oriented Big Data Analytics
Authors: Ahlem Abid, Farah Jemili
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Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine.Keywords: Apache Spark Streaming, Graph, Intrusion detection, k2 algorithm, Machine Learning, MAWILab, Microsoft Azure Cloud
Procedia PDF Downloads 1473769 Review of Different Machine Learning Algorithms
Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui
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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.Keywords: Data Mining, Web Mining, classification, ML Algorithms
Procedia PDF Downloads 3033768 Modern Imputation Technique for Missing Data in Linear Functional Relationship Model
Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, Rahmatullah Imon
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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in the LFRM. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators
Procedia PDF Downloads 3993767 Tank Barrel Surface Damage Detection Algorithm
Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský
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The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank
Procedia PDF Downloads 1373766 Generator Subgraphs of the Wheel
Authors: Neil M. Mame
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We consider only finite graphs without loops nor multiple edges. Let G be a graph with E(G) = {e1, e2, …., em}. The edge space of G, denoted by ε(G), is a vector space over the field Z2. The elements of ε(G) are all the subsets of E(G). Vector addition is defined as X+Y = X Δ Y, the symmetric difference of sets X and Y, for X, Y ∈ ε(G). Scalar multiplication is defined as 1.X =X and 0.X = Ø for X ∈ ε(G). The set S ⊆ ε(G) is called a generating set if every element ε(G) is a linear combination of the elements of S. For a non-empty set X ∈ ε(G), the smallest subgraph with edge set X is called edge-induced subgraph of G, denoted by G[X]. The set EH(G) = { A ∈ ε(G) : G[A] ≅ H } denotes the uniform set of H with respect to G and εH(G) denotes the subspace of ε(G) generated by EH(G). If εH(G) is generating set, then we call H a generator subgraph of G. This paper gives the characterization for the generator subgraphs of the wheel that contain cycles and gives the necessary conditions for the acyclic generator subgraphs of the wheel.Keywords: edge space, edge-induced subgraph, generator subgraph, wheel
Procedia PDF Downloads 4643765 An Engineering Application of the H-P Version of the Finite Element Method on Vibration Behavior of Rotors
Authors: Hadjoui Abdelhamid, Saimi Ahmed
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The hybrid h-p finite element method for the dynamic behavior of nonlinear rotors is described in this paper. The standard h-version method of discretizing the problem is retained, but modified to allow the use of polynomially-enriched beam elements. A hierarchically enriching element will thus not affect the nodal displacement and rotation, but will influence the values of the nodal bending moment and shear force is used. The deterministic movements of rotation and translation of the support which are coupled to the excitations due to unbalance are also taken into account. We study also the geometric dissymmetry of the shaft and the disc, thus the equations of motion of the rotor contain variable parametric coefficients over time that can lead to a lateral dynamic instability. The effects of movements combined support for bearings are analyzed and discussed through Campbell diagrams and spectral analyses. A program is made in Matlab. After validation of the program, several examples are studied. The influence of physical and geometric parameters on the natural frequencies of the shaft is determined through the study of these examples. Among these parameters, we include the variation in the diameter and the thickness of the rotor, the position of the disc.Keywords: Campbell diagram, critical speeds, nonlinear rotor, version h-p of FEM
Procedia PDF Downloads 2333764 DCT and Stream Ciphers for Improved Image Encryption Mechanism
Authors: T. R. Sharika, Ashwini Kumar, Kamal Bijlani
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Encryption is the process of converting crucial information’s unreadable to unauthorized persons. Image security is an important type of encryption that secures all type of images from cryptanalysis. A stream cipher is a fast symmetric key algorithm which is used to convert plaintext to cipher text. In this paper we are proposing an image encryption algorithm with Discrete Cosine Transform and Stream Ciphers that can improve compression of images and enhanced security. The paper also explains the use of a shuffling algorithm for enhancing securing.Keywords: decryption, DCT, encryption, RC4 cipher, stream cipher
Procedia PDF Downloads 3623763 Dual-Channel Multi-Band Spectral Subtraction Algorithm Dedicated to a Bilateral Cochlear Implant
Authors: Fathi Kallel, Ahmed Ben Hamida, Christian Berger-Vachon
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In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources.Keywords: speech enhancement, spectral substracion, noise estimation, cochlear impalnt
Procedia PDF Downloads 5493762 Recognition of Tifinagh Characters with Missing Parts Using Neural Network
Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui
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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN
Procedia PDF Downloads 3343761 Reliability Improvement of Power System Networks Using Adaptive Genetic Algorithm
Authors: Alireza Alesaadi
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Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed.Keywords: reliability, adaptive genetic algorithm, electrical network, communication engineering
Procedia PDF Downloads 5093760 Design Data Sorter Circuit Using Insertion Sorting Algorithm
Authors: Hoda Abugharsa
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In this paper we propose to design a sorter circuit using insertion sorting algorithm. The circuit will be designed using Algorithmic State Machines (ASM) method. That means converting the insertion sorting flowchart into an ASM chart. Then the ASM chart will be used to design the sorter circuit and the control unit.Keywords: insert sorting algorithm, ASM chart, sorter circuit, state machine, control unit
Procedia PDF Downloads 4453759 Analysis of Behaviors of Single and Group Helical Piles in Sands from Experiment Results
Authors: Jongho Park, Junwon Lee, Byeonghyun Choi, Kicheol Lee, Dongwook Kim
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The typically-used oil sand plant foundations are driven pile or drilled shaft. With more strict environmental regulations world widely, it became more important to completely remove the foundation during the stage of plant demolition. However, it is difficult to remove driven piles or drilled shafts that are installed at a deeper and stronger depth to gain more bearing pile capacity. The helical pile can be easily removed after its use and recycled; therefore it is suitable for oil sand plant foundation. This study analyzes the behavior of helical piles in sands. Axial pile load tests were carried out the varying spacing of helix plates (helices), rotation speed and weight of axial loading during pile installation. From the experiments, optimal helix plate spacing, rotation speed, axial loading during installation were determined. In addition, the behavior of helical pile groups was examined varying pile spacing. Finally, the behavior of single helical piles and that of group helical piles were compared.Keywords: oil sand plant, pile load test, helical pile, group helical pile, behavior
Procedia PDF Downloads 1673758 Automatic Classification Using Dynamic Fuzzy C Means Algorithm and Mathematical Morphology: Application in 3D MRI Image
Authors: Abdelkhalek Bakkari
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Image segmentation is a critical step in image processing and pattern recognition. In this paper, we proposed a new robust automatic image classification based on a dynamic fuzzy c-means algorithm and mathematical morphology. The proposed segmentation algorithm (DFCM_MM) has been applied to MR perfusion images. The obtained results show the validity and robustness of the proposed approach.Keywords: segmentation, classification, dynamic, fuzzy c-means, MR image
Procedia PDF Downloads 4793757 Autonomous Control of Ultrasonic Transducer Drive System
Authors: Dong-Keun Jeong, Jong-Hyun Kim, Woon-Ha Yoon, Hee-Je Kim
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In order to automatically operate the ultrasonic transducer drive system for sonicating aluminum, this paper proposes the ultrasonic transducer sensorless control algorithm. The resonance frequency shift and electrical impedance change is a common phenomenon in the state of the ultrasonic transducer. The proposed control algorithm make use of the impedance change of ultrasonic transducer according to the environment between air state and aluminum alloy state, it controls the ultrasonic transducer drive system autonomous without a sensor. The proposed sensorless autonomous ultrasonic transducer control algorithm was experimentally verified using a 3kW prototype ultrasonic transducer drive system.Keywords: ultrasonic transducer drive system, impedance change, sensorless, autonomous control algorithm
Procedia PDF Downloads 3603756 Detect Circles in Image: Using Statistical Image Analysis
Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee
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The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.Keywords: image processing, median filter, projection, scale-space, segmentation, threshold
Procedia PDF Downloads 4323755 Using Self Organizing Feature Maps for Automatic Prostate Segmentation in TRUS Images
Authors: Ahad Salimi, Hassan Masoumi
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Prostate cancer is one of the most common recognized cancers in men, and, is one of the most important mortality factors of cancer in this group. Determining of prostate’s boundary in TRUS (Transrectal Ultra Sound) images is very necessary for prostate cancer treatments. The weakness edges and speckle noise make the ultrasound images inherently to segment. In this paper a new automatic algorithm for prostate segmentation in TRUS images proposed that include three main stages. At first morphological smoothing and sticks filtering are used for noise removing. In second step, for finding a point in prostate region, SOFM algorithm is enlisted and in the last step, the boundary of prostate extracting accompanying active contour is employed. For validation of proposed method, a number of experiments are conducted. The results obtained by our algorithm show the promise of the proposed algorithm.Keywords: SOFM, preprocessing, GVF contour, segmentation
Procedia PDF Downloads 3303754 One-Dimension Model for Positive Displacement Pump with Cavitation Algorithm
Authors: Francesco Rizzuto, Matthew Stickland, Stephan Hannot
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The simulation of a positive displacement pump system with commercial software for Computer Fluid Dynamics (CFD), will result in an enormous computational effort due to the complexity of the pump system. This drawback restricts the use of it to a specific part of the pump in one simulation. This research focuses on developing an algorithm that provides a suitable result in agreement with experiment data, without that computational effort. The compressible equations are solved with an explicit algorithm. A comparison is presented between the FV method with Monotonic Upwind scheme for Conservative Laws (MUSCL) with slope limiter and experimental results. The source term for cavitation and friction is introduced into the algorithm with a slipping strategy and solved with a 4th order Runge-Kutta scheme (RK4). Different pumps are modeled and analyzed to evaluate the flexibility of the code. The simulation required minimal computation time and resources without compromising the accuracy of the simulation results. Therefore, this algorithm highlights the feasibility of pressure pulsation simulation as a design tool for an industrial purpose.Keywords: cavitation, diaphragm, DVCM, finite volume, MUSCL, positive displacement pump
Procedia PDF Downloads 1553753 Improving Temporal Correlations in Empirical Orthogonal Function Expansions for Data Interpolating Empirical Orthogonal Function Algorithm
Authors: Ping Bo, Meng Yunshan
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Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter
Procedia PDF Downloads 3243752 Physics of Black Holes. A Closed Cycle of Transformation of Matter in the Universe
Authors: Igor V. Kuzminov
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The proposed article is a development of the topics of gravity, the inverse temperature dependence of gravity, the action of the inverse temperature dependence of gravity, and the second law of thermodynamics, dark matter, the identity of gravity, inertial forces, and centrifugal forces. All interaction schemes are built on the basis of Newton's laws of classical mechanics and Rutherford's planetary model of the structure of the atom. The basis of all constructions is the gyroscopic effect of rotation of all particles of the atomic structure. In this case, interatomic and intermolecular bonds are accepted as the static part of the gyroscope, and the rotation of an electron in an atom is accepted as the dynamic part. The structure of the planet Earth is accepted as a model of the structure of the Black Hole. Namely, gravitational and thermodynamic phenomena in the structure of the planet Earth are accepted as a model. Based on this model, assumptions are made about the processes inside the Black Hole. Moreover, a version is put forward, a scheme of a closed cycle of transformation of matter in the Universe.Keywords: black hole, gravity, inverse temperature dependence of gravitational forces, second law of thermodynamics, gyroscopic effect, dark matter
Procedia PDF Downloads 253751 Multi-Level Priority Based Task Scheduling Algorithm for Workflows in Cloud Environment
Authors: Anju Bala, Inderveer Chana
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Task scheduling is the key concern for the execution of performance-driven workflow applications. As efficient scheduling can have major impact on the performance of the system, task scheduling is often chosen for assigning the request to resources in an efficient way based on cloud resource characteristics. In this paper, priority based task scheduling algorithm has been proposed that prioritizes the tasks based on the length of the instructions. The proposed scheduling approach prioritize the tasks of Cloud applications according to the limits set by six sigma control charts based on dynamic threshold values. Further, the proposed algorithm has been validated through the CloudSim toolkit. The experimental results demonstrate that the proposed algorithm is effective for handling multiple task lists from workflows and in considerably reducing Makespan and Execution time.Keywords: cloud computing, priority based scheduling, task scheduling, VM allocation
Procedia PDF Downloads 5173750 A Coordinate-Based Heuristic Route Search Algorithm for Delivery Truck Routing Problem
Authors: Ahmed Tarek, Ahmed Alveed
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Vehicle routing problem is a well-known re-search avenue in computing. Modern vehicle routing is more focused with the GPS-based coordinate system, as the state-of-the-art vehicle, and trucking systems are equipped with digital navigation. In this paper, a new two dimensional coordinate-based algorithm for addressing the vehicle routing problem for a supply chain network is proposed and explored, and the algorithm is compared with other available, and recently devised heuristics. For the algorithms discussed, which includes the pro-posed coordinate-based search heuristic as well, the advantages and the disadvantages associated with the heuristics are explored. The proposed algorithm is studied from the stand point of a small supermarket chain delivery network that supplies to its stores in four different states around the East Coast area, and is trying to optimize its trucking delivery cost. Minimizing the delivery cost for the supply network of a supermarket chain is important to ensure its business success.Keywords: coordinate-based optimal routing, Hamiltonian Circuit, heuristic algorithm, traveling salesman problem, vehicle routing problem
Procedia PDF Downloads 1473749 A Weighted K-Medoids Clustering Algorithm for Effective Stability in Vehicular Ad Hoc Networks
Authors: Rejab Hajlaoui, Tarek Moulahi, Hervé Guyennet
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In a highway scenario, the vehicle speed can exceed 120 kmph. Therefore, any vehicle can enter or leave the network within a very short time. This mobility adversely affects the network connectivity and decreases the life time of all established links. To ensure an effective stability in vehicular ad hoc networks with minimum broadcasting storm, we have developed a weighted algorithm based on the k-medoids clustering algorithm (WKCA). Indeed, the number of clusters and the initial cluster heads will not be selected randomly as usual, but considering the available transmission range and the environment size. Then, to ensure optimal assignment of nodes to clusters in both k-medoids phases, the combined weight of any node will be computed according to additional metrics including direction, relative speed and proximity. Empirical results prove that in addition to the convergence speed that characterizes the k-medoids algorithm, our proposed model performs well both AODV-Clustering and OLSR-Clustering protocols under different densities and velocities in term of end-to-end delay, packet delivery ratio, and throughput.Keywords: communication, clustering algorithm, k-medoids, sensor, vehicular ad hoc network
Procedia PDF Downloads 2383748 Experimental Investigations on the Mechanism of Stratified Liquid Mixing in a Cylinder
Authors: Chai Mingming, Li Lei, Lu Xiaoxia
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In this paper, the mechanism of stratified liquids’ mixing in a cylinder is investigated. It is focused on the effects of Rayleigh-Taylor Instability (RTI) and rotation of the cylinder on liquid interface mixing. For miscible liquids, Planar Laser Induced Fluorescence (PLIF) technique is applied to record the concentration field for one liquid. Intensity of Segregation (IOS) is used to describe the mixing status. For immiscible liquids, High Speed Camera is adopted to record the development of the interface. The experiment of RTI indicates that it plays a great role in the mixing process, and meanwhile the large-scale mixing is triggered, and subsequently the span of the stripes decreases, showing that the mesoscale mixing is coming into being. The rotation experiments show that the spin-down process has a great role in liquid mixing, during which the upper liquid falls down rapidly along the wall and crashes into the lower liquid. During this process, a lot of interface instabilities are excited. Liquids mix rapidly in the spin-down process. It can be concluded that no matter what ways have been adopted to speed up liquid mixing, the fundamental reason is the interface instabilities which increase the area of the interface between liquids and increase the relative velocity of the two liquids.Keywords: interface instability, liquid mixing, Rayleigh-Taylor Instability, spin-down process, spin-up process
Procedia PDF Downloads 3013747 Cost Effective Real-Time Image Processing Based Optical Mark Reader
Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar
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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding
Procedia PDF Downloads 1733746 Sweepline Algorithm for Voronoi Diagram of Polygonal Sites
Authors: Dmitry A. Koptelov, Leonid M. Mestetskiy
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Voronoi Diagram (VD) of finite set of disjoint simple polygons, called sites, is a partition of plane into loci (for each site at the locus) – regions, consisting of points that are closer to a given site than to all other. Set of polygons is a universal model for many applications in engineering, geoinformatics, design, computer vision, and graphics. VD of polygons construction usually done with a reduction to task of constructing VD of segments, for which there are effective O(n log n) algorithms for n segments. Preprocessing – constructing segments from polygons’ sides, and postprocessing – polygon’s loci construction by merging the loci of the sides of each polygon are also included in reduction. This approach doesn’t take into account two specific properties of the resulting segment sites. Firstly, all this segments are connected in pairs in the vertices of the polygons. Secondly, on the one side of each segment lies the interior of the polygon. The polygon is obviously included in its locus. Using this properties in the algorithm for VD construction is a resource to reduce computations. The article proposes an algorithm for the direct construction of VD of polygonal sites. Algorithm is based on sweepline paradigm, allowing to effectively take into account these properties. The solution is performed based on reduction. Preprocessing is the constructing of set of sites from vertices and edges of polygons. Each site has an orientation such that the interior of the polygon lies to the left of it. Proposed algorithm constructs VD for set of oriented sites with sweepline paradigm. Postprocessing is a selecting of edges of this VD formed by the centers of empty circles touching different polygons. Improving the efficiency of the proposed sweepline algorithm in comparison with the general Fortune algorithm is achieved due to the following fundamental solutions: 1. Algorithm constructs only such VD edges, which are on the outside of polygons. Concept of oriented sites allowed to avoid construction of VD edges located inside the polygons. 2. The list of events in sweepline algorithm has a special property: the majority of events are connected with “medium” polygon vertices, where one incident polygon side lies behind the sweepline and the other in front of it. The proposed algorithm processes such events in constant time and not in logarithmic time, as in the general Fortune algorithm. The proposed algorithm is fully implemented and tested on a large number of examples. The high reliability and efficiency of the algorithm is also confirmed by computational experiments with complex sets of several thousand polygons. It should be noted that, despite the considerable time that has passed since the publication of Fortune's algorithm in 1986, a full-scale implementation of this algorithm for an arbitrary set of segment sites has not been made. The proposed algorithm fills this gap for an important special case - a set of sites formed by polygons.Keywords: voronoi diagram, sweepline, polygon sites, fortunes' algorithm, segment sites
Procedia PDF Downloads 1773745 Real Time Video Based Smoke Detection Using Double Optical Flow Estimation
Authors: Anton Stadler, Thorsten Ike
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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.Keywords: low density, optical flow, upward smoke motion, video based smoke detection
Procedia PDF Downloads 3553744 Anomaly Detection Based Fuzzy K-Mode Clustering for Categorical Data
Authors: Murat Yazici
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Anomalies are irregularities found in data that do not adhere to a well-defined standard of normal behavior. The identification of outliers or anomalies in data has been a subject of study within the statistics field since the 1800s. Over time, a variety of anomaly detection techniques have been developed in several research communities. The cluster analysis can be used to detect anomalies. It is the process of associating data with clusters that are as similar as possible while dissimilar clusters are associated with each other. Many of the traditional cluster algorithms have limitations in dealing with data sets containing categorical properties. To detect anomalies in categorical data, fuzzy clustering approach can be used with its advantages. The fuzzy k-Mode (FKM) clustering algorithm, which is one of the fuzzy clustering approaches, by extension to the k-means algorithm, is reported for clustering datasets with categorical values. It is a form of clustering: each point can be associated with more than one cluster. In this paper, anomaly detection is performed on two simulated data by using the FKM cluster algorithm. As a significance of the study, the FKM cluster algorithm allows to determine anomalies with their abnormality degree in contrast to numerous anomaly detection algorithms. According to the results, the FKM cluster algorithm illustrated good performance in the anomaly detection of data, including both one anomaly and more than one anomaly.Keywords: fuzzy k-mode clustering, anomaly detection, noise, categorical data
Procedia PDF Downloads 53