Search results for: Computer aided detection (CAD)
2341 Low Cost Real Time Robust Identification of Impulsive Signals
Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman
Abstract:
This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.
Keywords: Sound Detection, Impulsive Signal, Background Noise, Neural Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23242340 Automatic Thresholding for Data Gap Detection for a Set of Sensors in Instrumented Buildings
Authors: Houda Najeh, Stéphane Ploix, Mahendra Pratap Singh, Karim Chabir, Mohamed Naceur Abdelkrim
Abstract:
Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors.Keywords: Building system, time series, diagnosis, outliers, delay, data gap.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8822339 Basic Study of Mammographic Image Magnification System with Eye-Detector and Simple EEG Scanner
Authors: A. Umemuro, M. Sato, M. Narita, S. Hori, S. Sakurai, T. Nakayama, A. Nakazawa, T. Ogura
Abstract:
Mammography requires the detection of very small calcifications, and physicians search for microcalcifications by magnifying the images as they read them. The mouse is necessary to zoom in on the images, but this can be tiring and distracting when many images are read in a single day. Therefore, an image magnification system combining an eye-detector and a simple electroencephalograph (EEG) scanner was devised, and its operability was evaluated. Two experiments were conducted in this study: the measurement of eye-detection error using an eye-detector and the measurement of the time required for image magnification using a simple EEG scanner. Eye-detector validation showed that the mean distance of eye-detection error ranged from 0.64 cm to 2.17 cm, with an overall mean of 1.24 ± 0.81 cm for the observers. The results showed that the eye detection error was small enough for the magnified area of the mammographic image. The average time required for point magnification in the verification of the simple EEG scanner ranged from 5.85 to 16.73 seconds, and individual differences were observed. The reason for this may be that the size of the simple EEG scanner used was not adjustable, so it did not fit well for some subjects. The use of a simple EEG scanner with size adjustment would solve this problem. Therefore, the image magnification system using the eye-detector and the simple EEG scanner is useful.
Keywords: EEG scanner, eye-detector, mammography, observers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3142338 A Combinatorial Model for ECG Interpretation
Authors: Costas S. Iliopoulos, Spiros Michalakopoulos
Abstract:
A new, combinatorial model for analyzing and inter- preting an electrocardiogram (ECG) is presented. An application of the model is QRS peak detection. This is demonstrated with an online algorithm, which is shown to be space as well as time efficient. Experimental results on the MIT-BIH Arrhythmia database show that this novel approach is promising. Further uses for this approach are discussed, such as taking advantage of its small memory requirements and interpreting large amounts of pre-recorded ECG data.Keywords: Combinatorics, ECG analysis, MIT-BIH Arrhythmia Database, QRS Detection, String Algorithms
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19242337 Evaluation of Introductory Programming Course for Non-Computer Science Majored Students
Authors: H. Varol
Abstract:
Although students’ interest level in pursuing Computer Science and related degrees are lower than previous decade, fundamentals of computers, specifically introductory level programming courses are either listed as core or elective courses for a number of non-computer science majors. Universities accommodate these non-computer science majored students either via creating separate sections of a class for them or simply offering mixed-body classroom solutions, in which both computer science and non-computer science students take the courses together. In this work, we demonstrated how we handle introductory level programming course at Sam Houston State University and also provide facts about our observations on students’ success during the coursework. Moreover, we provide suggestions and methodologies that are based on students’ major and skills to overcome the deficiencies of mix-body type of classes.
Keywords: Computer science, non-computer science major, programming, programming education.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18202336 Multimedia Data Fusion for Event Detection in Twitter by Using Dempster-Shafer Evidence Theory
Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan
Abstract:
Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.Keywords: Data fusion, Dempster-Shafer theory, data mining, event detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17892335 Topology-Based Character Recognition Method for Coin Date Detection
Authors: Xingyu Pan, Laure Tougne
Abstract:
For recognizing coins, the graved release date is important information to identify precisely its monetary type. However, reading characters in coins meets much more obstacles than traditional character recognition tasks in the other fields, such as reading scanned documents or license plates. To address this challenging issue in a numismatic context, we propose a training-free approach dedicated to detection and recognition of the release date of the coin. In the first step, the date zone is detected by comparing histogram features; in the second step, a topology-based algorithm is introduced to recognize coin numbers with various font types represented by binary gradient map. Our method obtained a recognition rate of 92% on synthetic data and of 44% on real noised data.
Keywords: Coin, detection, character recognition, topology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14562334 Enhanced Traffic Light Detection Method Using Geometry Information
Authors: Changhwan Choi, Yongwan Park
Abstract:
In this paper, we propose a method that allows faster and more accurate detection of traffic lights by a vision sensor during driving, DGPS is used to obtain physical location of a traffic light, extract from the image information of the vision sensor only the traffic light area at this location and ascertain if the sign is in operation and determine its form. This method can solve the problem in existing research where low visibility at night or reflection under bright light makes it difficult to recognize the form of traffic light, thus making driving unstable. We compared our success rate of traffic light recognition in day and night road environments. Compared to previous researches, it showed similar performance during the day but 50% improvement at night.
Keywords: Traffic light, Intelligent vehicle, Night, Detection, DGPS (Differential Global Positioning System).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24072333 Video Data Mining based on Information Fusion for Tamper Detection
Authors: Girija Chetty, Renuka Biswas
Abstract:
In this paper, we propose novel algorithmic models based on information fusion and feature transformation in crossmodal subspace for different types of residue features extracted from several intra-frame and inter-frame pixel sub-blocks in video sequences for detecting digital video tampering or forgery. An evaluation of proposed residue features – the noise residue features and the quantization features, their transformation in cross-modal subspace, and their multimodal fusion, for emulated copy-move tamper scenario shows a significant improvement in tamper detection accuracy as compared to single mode features without transformation in cross-modal subspace.Keywords: image tamper detection, digital forensics, correlation features image fusion
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18842332 A Structural Support Vector Machine Approach for Biometric Recognition
Authors: Vishal Awasthi, Atul Kumar Agnihotri
Abstract:
Face is a non-intrusive strong biometrics for identification of original and dummy facial by different artificial means. Face recognition is extremely important in the contexts of computer vision, psychology, surveillance, pattern recognition, neural network, content based video processing. The availability of a widespread face database is crucial to test the performance of these face recognition algorithms. The openly available face databases include face images with a wide range of poses, illumination, gestures and face occlusions but there is no dummy face database accessible in public domain. This paper presents a face detection algorithm based on the image segmentation in terms of distance from a fixed point and template matching methods. This proposed work is having the most appropriate number of nodal points resulting in most appropriate outcomes in terms of face recognition and detection. The time taken to identify and extract distinctive facial features is improved in the range of 90 to 110 sec. with the increment of efficiency by 3%.Keywords: Face recognition, Principal Component Analysis, PCA, Linear Discriminant Analysis, LDA, Improved Support Vector Machine, iSVM, elastic bunch mapping technique.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4612331 A Survey in Techniques for Imbalanced Intrusion Detection System Datasets
Authors: Najmeh Abedzadeh, Matthew Jacobs
Abstract:
An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms.
Keywords: IDS, intrusion detection system, imbalanced datasets, sampling algorithms, big data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10842330 Skin Detection using Histogram depend on the Mean Shift Algorithm
Authors: Soo- Young Ye, Ki-Gon Nam, Ki-Won Byun
Abstract:
In this paper, we were introduces a skin detection method using a histogram approximation based on the mean shift algorithm. The proposed method applies the mean shift procedure to a histogram of a skin map of the input image, generated by comparison with standard skin colors in the CbCr color space, and divides the background from the skin region by selecting the maximum value according to brightness level. The proposed method detects the skin region using the mean shift procedure to determine a maximum value that becomes the dividing point, rather than using a manually selected threshold value, as in existing techniques. Even when skin color is contaminated by illumination, the procedure can accurately segment the skin region and the background region. The proposed method may be useful in detecting facial regions as a pretreatment for face recognition in various types of illumination.Keywords: Skin region detection, mean shift, histogram approximation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22462329 A Procedure for Post-Earthquake Damage Estimation Based on Detection of High-Frequency Transients
Authors: Aleksandar Zhelyazkov, Daniele Zonta, Helmut Wenzel, Peter Furtner
Abstract:
In the current research structural health monitoring is considered for addressing the critical issue of post-earthquake damage detection. A non-standard approach for damage detection via acoustic emission is presented - acoustic emissions are monitored in the low frequency range (up to 120 Hz). Such emissions are termed high-frequency transients. Further a damage indicator defined as the Time-Ratio Damage Indicator is introduced. The indicator relies on time-instance measurements of damage initiation and deformation peaks. Based on the time-instance measurements a procedure for estimation of the maximum drift ratio is proposed. Monitoring data is used from a shaking-table test of a full-scale reinforced concrete bridge pier. Damage of the experimental column is successfully detected and the proposed damage indicator is calculated.Keywords: Acoustic emission, Damage detection, Shaking table test, Structural health monitoring, High-frequency transients.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10322328 Applying Wavelet Transform to Ferroresonance Detection and Protection
Authors: Chun-Wei Huang, Jyh-Cherng Gu, Ming-Ta Yang
Abstract:
Non-synchronous breakage or line failure in power systems with light or no loads can lead to core saturation in transformers or potential transformers. This can cause component and capacitance matching resulting in the formation of resonant circuits, which trigger ferroresonance. This study employed a wavelet transform for the detection of ferroresonance. Simulation results demonstrate the efficacy of the proposed method.
Keywords: Ferroresonance, Wavelet Transform, Intelligent Electronic Device, Transformer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16452327 Interference Reduction Technique in Multistage Multiuser Detector for DS-CDMA System
Authors: Lokesh Tharani, R.P.Yadav
Abstract:
This paper presents the results related to the interference reduction technique in multistage multiuser detector for asynchronous DS-CDMA system. To meet the real-time requirements for asynchronous multiuser detection, a bit streaming, cascade architecture is used. An asynchronous multiuser detection involves block-based computations and matrix inversions. The paper covers iterative-based suboptimal schemes that have been studied to decrease the computational complexity, eliminate the need for matrix inversions, decreases the execution time, reduces the memory requirements and uses joint estimation and detection process that gives better performance than the independent parameter estimation method. The stages of the iteration use cascaded and bits processed in a streaming fashion. The simulation has been carried out for asynchronous DS-CDMA system by varying one parameter, i.e., number of users. The simulation result exhibits that system gives optimum bit error rate (BER) at 3rd stage for 15-users.Keywords: Multi-user detection (MUD), multiple accessinterference (MAI), near-far effect, decision feedback detector, successive interference cancellation detector (SIC) and parallelinterference cancellation (PIC) detector.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17512326 Surface Charge Based Rapid Method for Detection of Microbial Contamination in Drinking Water and Food Products
Authors: Kandpal M. , Gundampati R. K , Debnath M.
Abstract:
Microbial contamination, most of which are fecal born in drinking water and food industry is a serious threat to humans. Escherichia coli is one of the most common and prevalent among them. We have developed a sensor for rapid and an early detection of contaminants, taking E.coli as a threat indicator organism. The sensor is based on co-polymerizations of aniline and formaldehyde in form of thin film over glass surface using the vacuum deposition technique. The particular doping combination of thin film with Fe-Al and Fe-Cu in different concentrations changes its non conducting properties to p- type semi conductor. This property is exploited to detect the different contaminants, believed to have the different surface charge. It was found through experiments that different microbes at same OD (0.600 at 600 nm) have different conductivity in solution. Also the doping concentration is found to be specific for attracting microbes on the basis of surface charge. This is a simple, cost effective and quick detection method which not only decreases the measurement time but also gives early warnings for highly contaminated samples.
Keywords: Sensor, Vacuum deposition technique, thin film, E.coli detection, doping concentration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15782325 Fast and Efficient Algorithms for Evaluating Uniform and Nonuniform Lagrange and Newton Curves
Authors: Taweechai Nuntawisuttiwong, Natasha Dejdumrong
Abstract:
Newton-Lagrange Interpolations are widely used in numerical analysis. However, it requires a quadratic computational time for their constructions. In computer aided geometric design (CAGD), there are some polynomial curves: Wang-Ball, DP and Dejdumrong curves, which have linear time complexity algorithms. Thus, the computational time for Newton-Lagrange Interpolations can be reduced by applying the algorithms of Wang-Ball, DP and Dejdumrong curves. In order to use Wang-Ball, DP and Dejdumrong algorithms, first, it is necessary to convert Newton-Lagrange polynomials into Wang-Ball, DP or Dejdumrong polynomials. In this work, the algorithms for converting from both uniform and non-uniform Newton-Lagrange polynomials into Wang-Ball, DP and Dejdumrong polynomials are investigated. Thus, the computational time for representing Newton-Lagrange polynomials can be reduced into linear complexity. In addition, the other utilizations of using CAGD curves to modify the Newton-Lagrange curves can be taken.Keywords: Newton interpolation, Lagrange interpolation, linear complexity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6012324 Real Time Lidar and Radar High-Level Fusion for Obstacle Detection and Tracking with Evaluation on a Ground Truth
Authors: Hatem Hajri, Mohamed-Cherif Rahal
Abstract:
Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions. Sensor fusion between Lidar and Radar aims at improving obstacle detection using advantages of the two sensors. The present paper proposes a real-time Lidar/Radar data fusion algorithm for obstacle detection and tracking based on the global nearest neighbour standard filter (GNN). This algorithm is implemented and embedded in an automative vehicle as a component generated by a real-time multisensor software. The benefits of data fusion comparing with the use of a single sensor are illustrated through several tracking scenarios (on a highway and on a bend) and using real-time kinematic sensors mounted on the ego and tracked vehicles as a ground truth.Keywords: Ground truth, Hungarian algorithm, lidar Radar data fusion, global nearest neighbor filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9362323 Processor Scheduling on Parallel Computers
Authors: Mohammad S. Laghari, Gulzar A. Khuwaja
Abstract:
Many problems in computer vision and image processing present potential for parallel implementations through one of the three major paradigms of geometric parallelism, algorithmic parallelism and processor farming. Static process scheduling techniques are used successfully to exploit geometric and algorithmic parallelism, while dynamic process scheduling is better suited to dealing with the independent processes inherent in the process farming paradigm. This paper considers the application of parallel or multi-computers to a class of problems exhibiting spatial data characteristic of the geometric paradigm. However, by using processor farming paradigm, a dynamic scheduling technique is developed to suit the MIMD structure of the multi-computers. A hybrid scheme of scheduling is also developed and compared with the other schemes. The specific problem chosen for the investigation is the Hough transform for line detection.Keywords: Hough transforms, parallel computer, parallel paradigms, scheduling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16372322 The Customization of 3D Last Form Design Based On Weighted Blending
Authors: Shih-Wen Hsiao, Chu-Hsuan Lee, Rong-Qi Chen
Abstract:
When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.
Keywords: 3D last design, Customization, Reverse engineering, Weighted morphing, Shape blending.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21932321 An Improved Fast Video Clip Search Algorithm for Copy Detection using Histogram-based Features
Authors: Feifei Lee, Qiu Chen, Koji Kotani, Tadahiro Ohmi
Abstract:
In this paper, we present an improved fast and robust search algorithm for copy detection using histogram-based features for short MPEG video clips from large video database. There are two types of histogram features used to generate more robust features. The first one is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Another one is ordinal histogram feature which is robust to color distortion. Furthermore, by Combining with a temporal division method, the spatial and temporal features of the video sequence are integrated to realize fast and robust video search for copy detection. Experimental results show the proposed algorithm can detect the similar video clip more accurately and robust than conventional fast video search algorithm.Keywords: Fast search, Copy detection, Adjacent pixel intensity difference quantization (APIDQ), DC image, Histogram feature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14362320 A Modified Cross Correlation in the Frequency Domain for Fast Pattern Detection Using Neural Networks
Authors: Hazem M. El-Bakry, Qiangfu Zhao
Abstract:
Recently, neural networks have shown good results for detection of a certain pattern in a given image. In our previous papers [1-5], a fast algorithm for pattern detection using neural networks was presented. Such algorithm was designed based on cross correlation in the frequency domain between the input image and the weights of neural networks. Image conversion into symmetric shape was established so that fast neural networks can give the same results as conventional neural networks. Another configuration of symmetry was suggested in [3,4] to improve the speed up ratio. In this paper, our previous algorithm for fast neural networks is developed. The frequency domain cross correlation is modified in order to compensate for the symmetric condition which is required by the input image. Two new ideas are introduced to modify the cross correlation algorithm. Both methods accelerate the speed of the fast neural networks as there is no need for converting the input image into symmetric one as previous. Theoretical and practical results show that both approaches provide faster speed up ratio than the previous algorithm.Keywords: Fast Pattern Detection, Neural Networks, Modified Cross Correlation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17282319 Infrastructure means for Adaptive Camouflage
Authors: Jiri Barta, Albert Srnik
Abstract:
The paper deals with the perspectives and possibilities of "smart solutions" to critical infrastructure protection. It means that common computer aided technologies are used from the perspective of new, better protection of selected infrastructure objects. The paper is focused on the co-product of the Czech Defence Research Project - ADAPTIV. This project is carrying out by the University of Defence, Faculty of Economics and Management at the Department of Civil Protection. The project creates system and technology for adaptive cybernetic camouflage of armed forces objects, armaments, vehicles and troops and of mobilization infrastructure. These adaptive camouflage system and technology will be useful for army tactic activities protection and for decoys generation also. The fourth chapter of the paper concerns the possibilities of using the introduced technology to the protection of selected civil (economically important), critical infrastructure objects. The aim of this section is to introduce the scientific capabilities and potential of the University of Defence research results and solutions for the practice.Keywords: ADAPTIV, Adaptive camouflage technology, CAMouflage, Cybernetic Active Camouflage
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15292318 A Stereo Image Processing System for Visually Impaired
Authors: G. Balakrishnan, G. Sainarayanan, R. Nagarajan, Sazali Yaacob
Abstract:
This paper presents a review on vision aided systems and proposes an approach for visual rehabilitation using stereo vision technology. The proposed system utilizes stereo vision, image processing methodology and a sonification procedure to support blind navigation. The developed system includes a wearable computer, stereo cameras as vision sensor and stereo earphones, all moulded in a helmet. The image of the scene infront of visually handicapped is captured by the vision sensors. The captured images are processed to enhance the important features in the scene in front, for navigation assistance. The image processing is designed as model of human vision by identifying the obstacles and their depth information. The processed image is mapped on to musical stereo sound for the blind-s understanding of the scene infront. The developed method has been tested in the indoor and outdoor environments and the proposed image processing methodology is found to be effective for object identification.Keywords: Blind navigation, stereo vision, image processing, object preference, music tones.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40912317 Islanding Detection Techniques for Synchronous Distributed Generation
Authors: Bharti B. Parmar, Vivek J. Pandya
Abstract:
The issue of unintentional islanding detection of grid connected synchronous distributed generation (SDG) remains the most challenging task faced by the distributed generation (DG) industry as SDG is highly capable of prolonging an island. This paper gives an insight of anti-islanding detection techniques mainly applied for SDG. Different techniques conclude that it is challenging to point out a generic method for a distinct purpose as the application of particular practice depends on nature of the end use and system dependent elements. Also, the setup and operational cost affect the selection of anti-islanding technique to achieve minimal compromising between cost and system quality. A test bench is created in the MATLAB/Simulink® to demonstrate the results of a 33 kV system. The results are highly satisfactory and they are according to the current practices.
Keywords: Synchronous distributed generation, islanding, point of common coupling, loss of grid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10512316 An Overview of Islanding Detection Methods in Photovoltaic Systems
Authors: Wei Yee Teoh, Chee Wei Tan
Abstract:
The issue of unintentional islanding in PV grid interconnection still remains as a challenge in grid-connected photovoltaic (PV) systems. This paper discusses the overview of popularly used anti-islanding detection methods, practically applied in PV grid-connected systems. Anti-islanding methods generally can be classified into four major groups, which include passive methods, active methods, hybrid methods and communication base methods. Active methods have been the preferred detection technique over the years due to very small non-detected zone (NDZ) in small scale distribution generation. Passive method is comparatively simpler than active method in terms of circuitry and operations. However, it suffers from large NDZ that significantly reduces its performance. Communication base methods inherit the advantages of active and passive methods with reduced drawbacks. Hybrid method which evolved from the combination of both active and passive methods has been proven to achieve accurate anti-islanding detection by many researchers. For each of the studied anti-islanding methods, the operation analysis is described while the advantages and disadvantages are compared and discussed. It is difficult to pinpoint a generic method for a specific application, because most of the methods discussed are governed by the nature of application and system dependent elements. This study concludes that the setup and operation cost is the vital factor for anti-islanding method selection in order to achieve minimal compromising between cost and system quality.Keywords: Active method, hybrid method, islanding detection, passive method, photovoltaic (PV), utility method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 97422315 Optical Fish Tracking in Fishways using Neural Networks
Authors: Alvaro Rodriguez, Maria Bermudez, Juan R. Rabuñal, Jeronimo Puertas
Abstract:
One of the main issues in Computer Vision is to extract the movement of one or several points or objects of interest in an image or video sequence to conduct any kind of study or control process. Different techniques to solve this problem have been applied in numerous areas such as surveillance systems, analysis of traffic, motion capture, image compression, navigation systems and others, where the specific characteristics of each scenario determine the approximation to the problem. This paper puts forward a Computer Vision based algorithm to analyze fish trajectories in high turbulence conditions in artificial structures called vertical slot fishways, designed to allow the upstream migration of fish through obstructions in rivers. The suggested algorithm calculates the position of the fish at every instant starting from images recorded with a camera and using neural networks to execute fish detection on images. Different laboratory tests have been carried out in a full scale fishway model and with living fishes, allowing the reconstruction of the fish trajectory and the measurement of velocities and accelerations of the fish. These data can provide useful information to design more effective vertical slot fishways.
Keywords: Computer Vision, Neural Network, Fishway, Fish Trajectory, Tracking
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19902314 Thermalytix: An Advanced Artificial Intelligence Based Solution for Non-Contact Breast Screening
Authors: S. Sudhakar, Geetha Manjunath, Siva Teja Kakileti, Himanshu Madhu
Abstract:
Diagnosis of breast cancer at early stages has seen better clinical and survival outcomes. Survival rates in developing countries like India are very low due to accessibility and affordability issues of screening tests such as Mammography. In addition, Mammography is not much effective in younger women with dense breasts. This leaves a gap in current screening methods. Thermalytix is a new technique for detecting breast abnormality in a non-contact, non-invasive way. It is an AI-enabled computer-aided diagnosis solution that automates interpretation of high resolution thermal images and identifies potential malignant lesions. The solution is low cost, easy to use, portable and is effective in all age groups. This paper presents the results of a retrospective comparative analysis of Thermalytix over Mammography and Clinical Breast Examination for breast cancer screening. Thermalytix was found to have better sensitivity than both the tests, with good specificity as well. In addition, Thermalytix identified all malignant patients without palpable lumps.
Keywords: Breast Cancer Screening, Radiology, Thermalytix, Artificial Intelligence, Thermography.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27862313 A Comparison of YOLO Family for Apple Detection and Counting in Orchards
Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long
Abstract:
In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.
Keywords: Agricultural object detection, Deep learning, machine vision, YOLO family.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10652312 Decision Algorithm for Smart Airbag Deployment Safety Issues
Authors: Aini Hussain, M A Hannan, Azah Mohamed, Hilmi Sanusi, Burhanuddin Yeop Majlis
Abstract:
Airbag deployment has been known to be responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decisions. Therefore, the authorities and industries have been looking for more innovative and intelligent products to be realized for future enhancements in the vehicle safety systems (VSSs). Although the VSSs technologies have advanced considerably, they still face challenges such as how to avoid unnecessary and untimely airbag deployments that can be hazardous and fatal. Currently, most of the existing airbag systems deploy without regard to occupant size and position. As such, this paper will focus on the occupant and crash sensing performances due to frontal collisions for the new breed of so called smart airbag systems. It intends to provide a thorough discussion relating to the occupancy detection, occupant size classification, occupant off-position detection to determine safe distance zone for airbag deployment, crash-severity analysis and airbag decision algorithms via a computer modeling. The proposed system model consists of three main modules namely, occupant sensing, crash severity analysis and decision fusion. The occupant sensing system module utilizes the weight sensor to determine occupancy, classify the occupant size, and determine occupant off-position condition to compute safe distance for airbag deployment. The crash severity analysis module is used to generate relevant information pertinent to airbag deployment decision. Outputs from these two modules are fused to the decision module for correct and efficient airbag deployment action. Computer modeling work is carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes.Keywords: Crash severity analysis, occupant size classification, smart airbag, vehicle safety system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4100