Search results for: Fault Detection
1474 Ship Detection Requirements Analysis for Different Sea States: Validation on Real SAR Data
Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores
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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.Keywords: SAR, generalized gamma distribution, detection curves, radar detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11641473 Intrusion Detection Using a New Particle Swarm Method and Support Vector Machines
Authors: Essam Al Daoud
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Intrusion detection is a mechanism used to protect a system and analyse and predict the behaviours of system users. An ideal intrusion detection system is hard to achieve due to nonlinearity, and irrelevant or redundant features. This study introduces a new anomaly-based intrusion detection model. The suggested model is based on particle swarm optimisation and nonlinear, multi-class and multi-kernel support vector machines. Particle swarm optimisation is used for feature selection by applying a new formula to update the position and the velocity of a particle; the support vector machine is used as a classifier. The proposed model is tested and compared with the other methods using the KDD CUP 1999 dataset. The results indicate that this new method achieves better accuracy rates than previous methods.Keywords: Feature selection, Intrusion detection, Support vector machine, Particle swarm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19751472 Torque Based Selection of ANN for Fault Diagnosis of Wound Rotor Asynchronous Motor-Converter Association
Authors: Djalal Eddine Khodja, Boukhemis Chetate
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In this paper, an automatic system of diagnosis was developed to detect and locate in real time the defects of the wound rotor asynchronous machine associated to electronic converter. For this purpose, we have treated the signals of the measured parameters (current and speed) to use them firstly, as indicating variables of the machine defects under study and, secondly, as inputs to the Artificial Neuron Network (ANN) for their classification in order to detect the defect type in progress. Once a defect is detected, the interpretation system of information will give the type of the defect and its place of appearance.Keywords: Artificial Neuron Networks (ANN), Effective Value (RMS), Experimental results, Failure detection Indicating values, Motor-converter unit.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14881471 Integration of Seismic and Seismological Data Interpretation for Subsurface Structure Identification
Authors: Iftikhar Ahmed Satti, Wan Ismail Wan Yusoff
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The structural interpretation of a part of eastern Potwar (Missa Keswal) has been carried out with available seismological, seismic and well data. Seismological data contains both the source parameters and fault plane solution (FPS) parameters and seismic data contains ten seismic lines that were re-interpreted by using well data. Structural interpretation depicts two broad types of fault sets namely, thrust and back thrust faults. These faults together give rise to pop up structures in the study area and also responsible for many structural traps and seismicity. Seismic interpretation includes time and depth contour maps of Chorgali Formation while seismological interpretation includes focal mechanism solution (FMS), depth, frequency, magnitude bar graphs and renewal of Seismotectonic map. The Focal Mechanism Solutions (FMS) that surrounds the study area are correlated with the different geological and structural maps of the area for the determination of the nature of subsurface faults. Results of structural interpretation from both seismic and seismological data show good correlation. It is hoped that the present work will help in better understanding of the variations in the subsurface structure and can be a useful tool for earthquake prediction, planning of oil field and reservoir monitoring.Keywords: Focal mechanism solution (FMS), Fault plane solution (FPS), Reservoir monitoring, earthquake prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24691470 An Evaluation of Sag Detection Techniques for Fast Solid-State Electronic Transferring to Alternate Electrical Energy Sources
Authors: M. N. Moschakis, I. G. Andritsos, V. V. Dafopoulos, J. M. Prousalidis, E. S. Karapidakis
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This paper deals with the evaluation of different detection strategies used in power electronic devices as a critical element for an effective mitigation of voltage disturbances. The effectiveness of those detection schemes in the mitigation of disturbances such as voltage sags by a Solid-State Transfer Switch is evaluated through simulations. All critical parameters affecting their performance is analytically described and presented. Moreover, the effect of fast detection of sags on the overall performance of STS is analyzed and investigated.
Keywords: Faults (short-circuits), industrial engineering, power electronics, power quality, static transfer switch, voltage sags (or dips).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18771469 Short-Path Near-Infrared Laser Detection of Environmental Gases by Wavelength-Modulation Spectroscopy
Authors: Isao Tomita
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The detection of environmental gases, 12CO2, 13CO2, and CH4, using near-infrared semiconductor lasers with a short laser path length is studied by means of wavelength-modulation spectroscopy. The developed system is compact and has high sensitivity enough to detect the absorption peaks of isotopic 13CO2 of a 3-% CO2 gas at 2 μm with a path length of 2.4 m, where its peak size is two orders of magnitude smaller than that of the ordinary 12CO2 peaks. In addition, the detection of 12CO2 peaks of a 385-ppm (0.0385-%) CO2 gas in the air is made at 2 μm with a path length of 1.4 m. Furthermore, in pursuing the detection of an ancient environmental CH4 gas confined to a bubble in ice at the polar regions, measurements of the absorption spectrum for a trace gas of CH4 in a small area are attempted. For a 100-% CH4 gas trapped in a ∼ 1 mm3 glass container, the absorption peaks of CH4 are obtained at 1.65 μm with a path length of 3 mm, and also the gas pressure is extrapolated from the measured data.
Keywords: Environmental Gases, Near-Infrared Laser Detection, Wavelength-Modulation Spectroscopy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17381468 Edge Detection Algorithm Based on Wavelet De-nosing Applied tothe X-ray Image Enhancement of the Electric Equipment
Authors: Fei Xue, Hong Yu, Da-da Wang, Wei Zhang, Rong-min Zou, Xiao-lanCai
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The X-ray technology has been used in non-destructive evaluation in the Power System, in which a visual non-destructive inspection method for the electrical equipment is provided. However, lots of noise is existed in the images that are got from the X-ray digital images equipment. Therefore, the auto defect detection which based on these images will be very difficult to proceed. A theory on X-ray image de-noising algorithm based on wavelet transform is proposed in this paper. Then the edge detection algorithm is used so that the defect can be pushed out. The result of experiment shows that the method which utilized by this paper is very useful for de-noising on the X-ray images.
Keywords: de-noising, edge detection, wavelet transform, X-ray
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15361467 Supervisory Controller with Three-State Energy Saving Mode for Induction Motor in Fluid Transportation
Authors: O. S. Ebrahim, K. O. Shawky, M. O. Ebrahim, P. K. Jain
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Induction Motor (IM) driving pump is the main consumer of electricity in a typical fluid transportation system (FTS). Changing the connection of the stator windings from delta to star at no load can achieve noticeable active and reactive energy savings. This paper proposes a supervisory hysteresis liquid-level control with three-state energy saving mode (ESM) for IM in FTS including storage tank. The IM pump drive comprises modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to computer ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. A logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction, considering the motor thermal capacity used. An artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and, computer simulations are performed to show the effectiveness of the proposed control in terms of reliability, power quality and energy/coenergy cost reduction with the suggestion of power factor correction.
Keywords: Artificial Neural Network, ANN, Energy Saving Mode, ESM, Induction Motor, IM, star/delta switch, supervisory control, fluid transportation, reliability, power quality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3591466 An Efficient Fundamental Matrix Estimation for Moving Object Detection
Authors: Yeongyu Choi, Ju H. Park, S. M. Lee, Ho-Youl Jung
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In this paper, an improved method for estimating fundamental matrix is proposed. The method is applied effectively to monocular camera based moving object detection. The method consists of corner points detection, moving object’s motion estimation and fundamental matrix calculation. The corner points are obtained by using Harris corner detector, motions of moving objects is calculated from pyramidal Lucas-Kanade optical flow algorithm. Through epipolar geometry analysis using RANSAC, the fundamental matrix is calculated. In this method, we have improved the performances of moving object detection by using two threshold values that determine inlier or outlier. Through the simulations, we compare the performances with varying the two threshold values.
Keywords: Corner detection, optical flow, epipolar geometry, RANSAC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11111465 Challenges in Video Based Object Detection in Maritime Scenario Using Computer Vision
Authors: Dilip K. Prasad, C. Krishna Prasath, Deepu Rajan, Lily Rachmawati, Eshan Rajabally, Chai Quek
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This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here.Keywords: Autonomous maritime vehicle, object detection, situation awareness, tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13071464 A Dynamic Programming Model for Maintenance of Electric Distribution System
Authors: Juha Korpijärvi, Jari Kortelainen
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The paper presents dynamic programming based model as a planning tool for the maintenance of electric power systems. Every distribution component has an exponential age depending reliability function to model the fault risk. In the moment of time when the fault costs exceed the investment costs of the new component the reinvestment of the component should be made. However, in some cases the overhauling of the old component may be more economical than the reinvestment. The comparison between overhauling and reinvestment is made by optimisation process. The goal of the optimisation process is to find the cost minimising maintenance program for electric power distribution system.
Keywords: Dynamic programming, Electric distribution system, Maintenance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20911463 On the Verification of Power Nap Associated with Stage 2 Sleep and Its Application
Authors: Jetsada Arnin, Yodchanan Wongsawat
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One of the most important causes of accidents is driver fatigue. To reduce the accidental rate, the driver needs a quick nap when feeling sleepy. Hence, searching for the minimum time period of nap is a very challenging problem. The purpose of this paper is twofold, i.e. to investigate the possible fastest time period for nap and its relationship with stage 2 sleep, and to develop an automatic stage 2 sleep detection and alarm device. The experiment for this investigation is designed with 21 subjects. It yields the result that waking up the subjects after getting into stage 2 sleep for 3-5 minutes can efficiently reduce the sleepiness. Furthermore, the automatic stage 2 sleep detection and alarm device yields the real-time detection accuracy of approximately 85% which is comparable with the commercial sleep lab system.Keywords: Stage 2 sleep, nap, sleep detection, real-time, EEG
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14491462 A Novel Framework for Abnormal Behaviour Identification and Detection for Wireless Sensor Networks
Authors: Muhammad R. Ahmed, Xu Huang, Dharmendra Sharma
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Despite extensive study on wireless sensor network security, defending internal attacks and finding abnormal behaviour of the sensor are still difficult and unsolved task. The conventional cryptographic technique does not give the robust security or detection process to save the network from internal attacker that cause by abnormal behavior. The insider attacker or abnormally behaved sensor identificationand location detection framework using false massage detection and Time difference of Arrival (TDoA) is presented in this paper. It has been shown that the new framework can efficiently identify and detect the insider attacker location so that the attacker can be reprogrammed or subside from the network to save from internal attack.Keywords: Insider Attaker identification, Abnormal Behaviour, Location detection, Time difference of Arrival (TDoA), Wireless sensor network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17651461 Study on Crater Detection Using FLDA
Authors: Yoshiaki Takeda, Norifumi Aoyama, Takahiro Tanaami, Syouhei Honda, Kenta Tabata, Hiroyuki Kamata
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In this paper, we validate crater detection in moon surface image using FLDA. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) project aiming at the pin-point landing to the moon surface. The point where the lander should land is judged by the position relations of the craters obtained via camera, so the real-time image processing becomes important element. Besides, in the SLIM project, 400kg-class lander is assumed, therefore, high-performance computers for image processing cannot be equipped. We are studying various crater detection methods such as Haar-Like features, LBP, and PCA. And we think these methods are appropriate to the project, however, to identify the unlearned images obtained by actual is insufficient. In this paper, we examine the crater detection using FLDA, and compare with the conventional methods.
Keywords: Crater Detection, Fisher Linear Discriminant Analysis , Haar-Like Feature, Image Processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17201460 Building and Tree Detection Using Multiscale Matched Filtering
Authors: Abdullah H. Özcan, Dilara Hisar, Yetkin Sayar, Cem Ünsalan
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In this study, an automated building and tree detection method is proposed using DSM data and true orthophoto image. A multiscale matched filtering is used on DSM data. Therefore, first watershed transform is applied. Then, Otsu’s thresholding method is used as an adaptive threshold to segment each watershed region. Detected objects are masked with NDVI to separate buildings and trees. The proposed method is able to detect buildings and trees without entering any elevation threshold. We tested our method on ISPRS semantic labeling dataset and obtained promising results.Keywords: Building detection, tree detection, matched filtering, multiscale, local maximum filtering, watershed segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5371459 Face Detection using Variance based Haar-Like feature and SVM
Authors: Cuong Nguyen Khac, Ju H. Park, Ho-Youl Jung
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This paper proposes a new approach to perform the problem of real-time face detection. The proposed method combines primitive Haar-Like feature and variance value to construct a new feature, so-called Variance based Haar-Like feature. Face in image can be represented with a small quantity of features using this new feature. We used SVM instead of AdaBoost for training and classification. We made a database containing 5,000 face samples and 10,000 non-face samples extracted from real images for learning purposed. The 5,000 face samples contain many images which have many differences of light conditions. And experiments showed that face detection system using Variance based Haar-Like feature and SVM can be much more efficient than face detection system using primitive Haar-Like feature and AdaBoost. We tested our method on two Face databases and one Non-Face database. We have obtained 96.17% of correct detection rate on YaleB face database, which is higher 4.21% than that of using primitive Haar-Like feature and AdaBoost.Keywords: AdaBoost, Haar-Like feature, SVM, variance, Variance based Haar-Like feature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37231458 Computer Aided Detection on Mammography
Authors: Giovanni Luca Masala
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A typical definition of the Computer Aided Diagnosis (CAD), found in literature, can be: A diagnosis made by a radiologist using the output of a computerized scheme for automated image analysis as a diagnostic aid. Often it is possible to find the expression Computer Aided Detection (CAD or CADe): this definition emphasizes the intent of CAD to support rather than substitute the human observer in the analysis of radiographic images. In this article we will illustrate the application of CAD systems and the aim of these definitions. Commercially available CAD systems use computerized algorithms for identifying suspicious regions of interest. In this paper are described the general CAD systems as an expert system constituted of the following components: segmentation / detection, feature extraction, and classification / decision making. As example, in this work is shown the realization of a Computer- Aided Detection system that is able to assist the radiologist in identifying types of mammary tumor lesions. Furthermore this prototype of station uses a GRID configuration to work on a large distributed database of digitized mammographic images.Keywords: Computer Aided Detection, Computer Aided Diagnosis, mammography, GRID.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19171457 Application of Neural Networks in Power Systems; A Review
Authors: M. Tarafdar Haque, A.M. Kashtiban
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The electric power industry is currently undergoing an unprecedented reform. One of the most exciting and potentially profitable recent developments is increasing usage of artificial intelligence techniques. The intention of this paper is to give an overview of using neural network (NN) techniques in power systems. According to the growth rate of NNs application in some power system subjects, this paper introduce a brief overview in fault diagnosis, security assessment, load forecasting, economic dispatch and harmonic analyzing. Advantages and disadvantages of using NNs in above mentioned subjects and the main challenges in these fields have been explained, too.
Keywords: Neural network, power system, security assessment, fault diagnosis, load forecasting, economic dispatch, harmonic analyzing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 77821456 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 18881455 Developing of Fragility Curve for Two-Span Simply Supported Concrete Bridge in Near-Fault Area
Authors: S. Shirazian, M.R. Ghayamghamian, G.R. Nouri
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Bridges are one of the main components of transportation networks. They should be functional before and after earthquake for emergency services. Therefore we need to assess seismic performance of bridges under different seismic loadings. Fragility curve is one of the popular tools in seismic evaluations. The fragility curves are conditional probability statements, which give the probability of a bridge reaching or exceeding a particular damage level for a given intensity level. In this study, the seismic performance of a two-span simply supported concrete bridge is assessed. Due to usual lack of empirical data, the analytical fragility curve was developed by results of the dynamic analysis of bridge subjected to the different time histories in near-fault area.Keywords: Fragility curve, Seismic behavior, Time historyanalysis, Transportation Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27821454 High Impedance Faults Detection Technique Based on Wavelet Transform
Authors: Ming-Ta Yang, Jin-Lung Guan, Jhy-Cherng Gu
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The purpose of this paper is to solve the problem of protecting aerial lines from high impedance faults (HIFs) in distribution systems. This investigation successfully applies 3I0 zero sequence current to solve HIF problems. The feature extraction system based on discrete wavelet transform (DWT) and the feature identification technique found on statistical confidence are then applied to discriminate effectively between the HIFs and the switch operations. Based on continuous wavelet transform (CWT) pattern recognition of HIFs is proposed, also. Staged fault testing results demonstrate that the proposed wavelet based algorithm is feasible performance well.Keywords: Continuous wavelet transform, discrete wavelet transform, high impedance faults, statistical confidence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23151453 An Improved Lattice Reduction Aided Detection Scheme for MIMO-OFDM System
Authors: Jang-Kyun Ahn, Seung-Jun Yu, Eui-Young Lee, Hyoung-Kyu Song
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This paper proposes an efficient lattice-reduction-aided detection (LRD) scheme to improve the detection performance of MIMO-OFDM system. In this proposed scheme, V candidate symbols are considered at the first layer, and V probable streams are detected with LRD scheme according to the first detected V candidate symbols. Then, the most probable stream is selected through a ML test. Since the proposed scheme can more accurately detect initial symbol and can reduce transmission of error to rest symbols, the proposed scheme shows more improved performance than conventional LRD with very low complexity.Keywords: Lattice reduction aided detection, MIMO-OFDM, QRD-M, V-BLAST.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17081452 Finding Sparse Features in Face Detection Using Genetic Algorithms
Authors: H. Sagha, S. Kasaei, E. Enayati, M. Dehghani
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Although Face detection is not a recent activity in the field of image processing, it is still an open area for research. The greatest step in this field is the work reported by Viola and its recent analogous is Huang et al. Both of them use similar features and also similar training process. The former is just for detecting upright faces, but the latter can detect multi-view faces in still grayscale images using new features called 'sparse feature'. Finding these features is very time consuming and inefficient by proposed methods. Here, we propose a new approach for finding sparse features using a genetic algorithm system. This method requires less computational cost and gets more effective features in learning process for face detection that causes more accuracy.Keywords: Face Detection, Genetic Algorithms, Sparse Feature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15711451 Implementation of Edge Detection Based on Autofluorescence Endoscopic Image of Field Programmable Gate Array
Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang
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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.
Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6491450 Gradual Shot Boundary Detection and Classification Based on Fractal Analysis
Authors: Zeinab Zeinalpour-Tabrizi, Faeze Asdaghi, Mahmooh Fathy, Mohammad Reza Jahed-Motlagh
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Shot boundary detection is a fundamental step for the organization of large video data. In this paper, we propose a new method for video gradual shots detection and classification, using advantages of fractal analysis and AIS-based classifier. Proposed features are “vertical intercept" and “fractal dimension" of each frame of videos which are computed using Fourier transform coefficients. We also used a classifier based on Clonal Selection Algorithm. We have carried out our solution and assessed it according to the TRECVID2006 benchmark dataset.
Keywords: shot boundary detection, gradual shots, fractal analysis, artificial immune system, choose Clooney.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19111449 Fingerprint on Ballistic after Shooting
Authors: Narong Kulnides
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This research involved fingerprints on ballistics after shooting. Two objectives of research were as follow; (1) to study the duration of the existence of latent fingerprints on .38, .45, 9 mm and .223 cartridge case after shooting, and (2) to compare the effectiveness of the detection of latent fingerprints by Black Powder, Super Glue, Perma Blue and Gun Bluing. The latent fingerprint appearance were studied on .38, .45, 9 mm. and .223 cartridge cases before and after shooting with Black Powder, Super Glue, Perma Blue and Gun Bluing. The detection times were 3 minute, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78 and 84 hours respectively. As a result of the study, it can be conclude that
- Before shooting, the detection of latent fingerprints on 38, .45, and 9 mm. and .223 cartridge cases with Black Powder, Super Glue, Perma Blue and Gun Bluing can detect the fingerprints at all detection times.
- After shooting, the detection of latent fingerprints on .38, .45, 9 mm. and .223 cartridge cases with Black Powder, Super Glue did not appear. The detection of latent fingerprints on .38, .45, 9 mm. cartridge cases with Perma Blue and Gun Bluing were found 100% of the time and the detection of latent fingerprints on .223 cartridge cases with Perma Blue and Gun Bluing were found 40% and 46.67% of the time, respectively.
Keywords: Ballistic, Fingerprint, Shooting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25831448 Surface Defects Detection for Ceramic Tiles UsingImage Processing and Morphological Techniques
Authors: H. Elbehiery, A. Hefnawy, M. Elewa
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Quality control in ceramic tile manufacturing is hard, labor intensive and it is performed in a harsh industrial environment with noise, extreme temperature and humidity. It can be divided into color analysis, dimension verification, and surface defect detection, which is the main purpose of our work. Defects detection is still based on the judgment of human operators while most of the other manufacturing activities are automated so, our work is a quality control enhancement by integrating a visual control stage using image processing and morphological operation techniques before the packing operation to improve the homogeneity of batches received by final users.
Keywords: Quality control, Defects detection, Visual control, Image processing, Morphological operation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 66171447 Advanced Polymorphic Techniques
Authors: Philippe Beaucamps
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Nowadays viruses use polymorphic techniques to mutate their code on each replication, thus evading detection by antiviruses. However detection by emulation can defeat simple polymorphism: thus metamorphic techniques are used which thoroughly change the viral code, even after decryption. We briefly detail this evolution of virus protection techniques against detection and then study the METAPHOR virus, today's most advanced metamorphic virus.
Keywords: Computer virus, Viral mutation, Polymorphism, Meta¬morphism, MetaPHOR, Virus history, Obfuscation, Viral genetic techniques.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24741446 Unsupervised Outlier Detection in Streaming Data Using Weighted Clustering
Authors: Yogita, Durga Toshniwal
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Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.
Keywords: Concept Evolution, Irrelevant Attributes, Streaming Data, Unsupervised Outlier Detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26231445 A New Method for Detection of Artificial Objects and Materials from Long Distance Environmental Images
Authors: H. Dujmic, V. Papic, H. Turic
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The article presents a new method for detection of artificial objects and materials from images of the environmental (non-urban) terrain. Our approach uses the hue and saturation (or Cb and Cr) components of the image as the input to the segmentation module that uses the mean shift method. The clusters obtained as the output of this stage have been processed by the decision-making module in order to find the regions of the image with the significant possibility of representing human. Although this method will detect various non-natural objects, it is primarily intended and optimized for detection of humans; i.e. for search and rescue purposes in non-urban terrain where, in normal circumstances, non-natural objects shouldn-t be present. Real world images are used for the evaluation of the method.Keywords: Landscape surveillance, mean shift algorithm, image segmentation, target detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1385