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Evaluation of Change detection algorithms using Difficulty Maps

IEEE LATIN AMERICA TRANSACTIONS 2023年第6期21卷 700-706页

作者： Sanches, Silvio Ricardo Rodrigues Correa, Cleber Gimenez Brum, Beatriz Regina Bugatti, Pedro Henrique Saito, Priscila Tiemi Maeda da Silva, Claudinei Moreira Custodio Junior, Elton Univ Tecnol Fed Parana Cornelio Procopio Brazil Univ Fed Sao Carlos Sao Carlos Brazil

The evaluation of a change detection algorithm should show its superiority over state-of-the-art algorithms' performances. Evaluating an algorithm involves executing it to segment a set of videos and comparing the results with the ground truth. Here, we used the difficulty level to classify each pixel of each frame of the videos of a dataset as an algorithm performance measure. A structure called "difficulty map" stores information about the difficulty of classifying each pixel in a frame. Based on these maps, we developed a metric that aims to evaluate the performance of algorithms on the difficulty map. The results showed that there are algorithms with the characteristic of classifying pixels that most state-of-the-art algorithms cannot classify (promising algorithms). Identifying such algorithms is essential since improving their performance means facing challenges already overcome by existing approaches.

关键词： Classification algorithms Videos detection algorithms Change detection algorithms IEEE transactions Monitoring Meteorology Algorithm evaluation change detection difficulty map video segmentation

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BIDIRECTIONAL RING-BASED TERMINATION detection algorithms FOR DISTRIBUTED COMPUTATIONS

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IEE PROCEEDINGS-E COMPUTERS AND DIGITAL TECHNIQUES 1989年第5期136卷 415-422页

作者： ARORA, RK GUPTA, MN Computer Services Center Indian Institute of Technology New Delhi India

An interesting and difficult problem in the area of distributed problem solving is that of detecting the termination of distributed programs soon after their assigned task is over. In a distributed environment, processes of a distributed program communicate only through exchange of messages and no process maintains complete information about the state of other processes. Additional efforts are, therefore, required to detect the situation when the processes of a distributed program complete their assigned task. The problem of detection of such a situation was first brought into prominence by N. Francez (1980). The problem requires taking snapshots over the states of the processes and then testing the termination criterion over these states. So far, reported algorithms can be broadly categorised into classes depending upon the topology employed namely a unidirectional ring, a spanning tree, and an arbitrary network. The authors explore yet another alternative in the form of bidirectional control communication around a ring. This type of communication potentially offers selective advantages of all the earlier approaches and depicts an approach lying between unidirectional communication and communication in all directions.

关键词： Communication Research less-favoured region Messages prominences Bidirectional termination criteria detection algorithms Distributed software distributed problem solving

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Designing Heavy-Hitter detection algorithms for Programmable Switches

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IEEE-ACM TRANSACTIONS ON NETWORKING 2020年第3期28卷 1172-1185页

作者： Ben Basat, Ran Chen, Xiaoqi Einziger, Gil Rottenstreich, Ori Harvard Univ Sch Engn & Appl Sci Cambridge MA 02138 USA Princeton Univ Dept Comp Sci Princeton NJ 08544 USA Ben Gurion Univ Negev Dept Comp Sci IL-84105 Beer Sheva Israel Technion IL-3200003 Haifa Israel

Programmable network switches promise flexibility and high throughput, enabling applications such as load balancing and traffic engineering. Network measurement is a fundamental building block for such applications, including tasks such as the identification of heavy hitters (largest flows) or the detection of traffic changes. However, high-throughput packet processing architectures place certain limitations on the programming model, such as restricted branching, limited capability for memory access, and a limited number of processing stages. These limitations restrict the types of measurement algorithms that can run on programmable switches. In this paper, we focus on the Reconfigurable Match Tables (RMT) programmable high-throughput switch architecture, and carefully examine its constraints on designing measurement algorithms. We demonstrate our findings while solving the heavy hitter problem. We introduce PRECISION, an algorithm that uses Partial Recirculation to find top flows on a programmable switch. By recirculating a small fraction of packets, PRECISION simplifies the access to stateful memory to conform with RMT limitations and achieves higher accuracy than previous heavy hitter detection algorithms that avoid recirculation. We also evaluate each of the adaptations made by PRECISION and analyze its effect on the measurement accuracy. Finally, we suggest two algorithms for the hierarchical heavy hitters detection problem in which the goal is identifying the subnets that send excessive traffic and are potentially malicious. To the best of our knowledge, our work is the first to do so on RMT switches.

关键词： Pipelines Throughput Memory management detection algorithms Task analysis Approximation algorithms Software defined networking measurement

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Simulation of CFAR detection algorithms for arbitrary clutter distributions

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IEE PROCEEDINGS-RADAR SONAR AND NAVIGATION 2000年第1期147卷 31-40页

作者： Srinivasan, R Ctr Airborne Syst Bangalore 560037 Karnataka India

Simulation and performance estimation methodologies are developed for constant false-alarm rate (CFAR) detection algorithms based on the powerful concept of importance sampling (IS). Such algorithms involve crossings of a random threshold. Compression of the threshold density function produces the required biasing to implement IS procedures. Adaptive optimisation of simulation estimators and estimation of detector threshold multipliers are described. Easily computable approximations for false-alarm probabilities (FAPs) of cell averaging (CA)-CFAR detectors are derived. Fast simulation results are described for examples with known clutter distributions. The practically important situation when clutter densities are unknown is dealt with. algorithms blind to the density and having appreciable gains over conventional Monte Carlo simulation are demonstrated. In a limited experiment these are shown to track a step change in clutter distribution. It is argued, albeit tentatively, that the procedures could point the way to implementation of estimators for FAPs and their control through threshold adaptation.

关键词： Estimators Monte Carlo technique simulating clutter Crossing step change detection algorithms importance sampling Simulation results

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A METHODOLOGY FOR QUANTITATIVE PERFORMANCE EVALUATION OF detection algorithms

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1995年第12期4卷 1667-1674页

作者： KANUNGO, T JAISIMHA, MY PALMER, J HARALICK, RM UNIV WASHINGTON DEPT PSYCHOLSEATTLEWA 98195

We present a methodology for the quantitative performance evaluation of detection algorithms in computer vision. A common method is to generate a variety of input images by varying the image parameters and evaluate the performance of the algorithm, as algorithm parameters vary. Operating curves that relate the probability of misdetection and false alarm are generated for each parameter setting. Such an analysis does not integrate the performance of the numerous operating curves. In this paper, we outline a methodology for summarizing many operating curves into a few performance curves. This methodology is adapted from the human psychophysics literature and is general to any detection algorithm. The central concept is to measure the effect of variables in terms of the equivalent effect of a critical signal variable, which in turn facilitates the determination of the breakdown point of the algorithm. We demonstrate the methodology by comparing the performance of two-line detection algorithms.

关键词： Image edge detection Gratings Task analysis detection algorithms Detectors Performance evaluation Signal to noise ratio

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A COMPARISON OF SUBOPTIMAL detection algorithms APPLIED TO THE ADDITIVE MIX OF ORTHOGONAL SINUSOIDAL SIGNALS

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IEEE TRANSACTIONS ON COMMUNICATIONS 1988年第5期36卷 538-543页

作者： MILUTINOVIC, V School of Electrical Engineering Purdue University West Lafayette IN USA

A comparison is made of the performance of three algorithms for suboptimal signal detection applied to an additive mix of orthogonal sinusoidal signals. The study considers zero-mean Gaussian noise and a number of different impairments found in related data communications media, including quantization effects, frequency-selective fading, and frequency shifts. It is shown that different procedures ran differently in the presence of different impairments, so that the final selection of the procedure to be implemented will depend on the characteristics of the communications environment.

关键词： Orthogonal physical impairment Quantization Additives detection algorithms signals signal acquisition data communication Sinusoidal Gaussian noise

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Pressure-detection algorithms A Suited Design

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IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 2009年第5期28卷 35-40页

作者： Perfetto, J. C. Ruiz, A. G. Sirne, R. O. D'Attellis, C. E. Univ Buenos Aires Inst Ingn Biomed IIBM RA-1053 Buenos Aires DF Argentina Fernandez Hosp Syncope Lab Hyderabad Andhra Pradesh India Univ Nacl San Martin Buenos Aires DF Argentina Univ Favaloro Buenos Aires DF Argentina

Our approach is based on identifying specific characteristics of the arterial blood pressure (ABP) signal. During the development of the algorithm, we examined the signals and tried to extract the features that signals always share with other signals of the same type. These features permit acceptance of a portion of the signal as being part of arterial pressure or reject it as being an artifact. The algorithm first detects the occurrence of the systolic point and, thereafter, the diastolic point. The method we present here is designed to be used in adaptation mechanisms of the cardiovascular system assessment.

关键词： Signal processing Multiresolution analysis Epilepsy System testing detection algorithms Electrocardiography Electroencephalography Signal resolution Pathology Cardiovascular system

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Efficient detection algorithms for multi-input/multi-output systems by exploiting the non-circularity of transmitted signal source

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IET SIGNAL PROCESSING 2011年第2期5卷 180-186页

作者： Ding, Y. Wang, Y. Diouris, J. -F. Univ Nantes Ecole Polytech Lab IREENA F-44306 Nantes France

In this study, several new detection algorithms are proposed for multi-input/multi-output (MIMO) communication systems transmitting non-circular signals. Unlike the conventional receivers, the proposed detectors estimate the transmitted signal from both the received signal and its complex conjugate version. Analytical results quantifying the performance improvement are provided. As a typical example, extended zero-forcing (EZF) detector and extended minimum mean square error (EMMSE) detector are derived for the real signals. Computational complexity of the proposed algorithms remains the same order as that of the conventional zero-forcing (ZF). Simulation results show that both EZF and EMMSE detectors significantly outperform the conventional minimum mean square error (MMSE) detector, and that the ordered-successive-interference-cancelling (OSIC) version of the EZF (or EMMSE) detector has a quasi-optimal performance in terms of bit error rate (BER).

关键词： Electromagnetic compatibility and interference bit error rate error statistics ordered-successive-interference-cancelling extended zero-forcing detector quasioptimal performance multiinput/multioutput systems interference suppression transmitting noncircular signals complex conjugate version mean square error methods detection algorithms extended minimum mean square error Interpolation and function approximation (numerical analysis) computational complexity BER Radio links and equipment transmitted signal source MIMO communication Other topics in statistics

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Quality Assessment Methods to Evaluate the Performance of Edge detection algorithms for Digital Image: A Systematic Literature Review

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IEEE ACCESS 2021年 9卷 87763-87776页

作者： Tariq, Nazish Hamzah, Rostam Affendi Ng, Theam Foo Wang, Shir Li Ibrahim, Haidi Univ Sains Malaysia Sch Elect & Elect Engn Engn Campus Nibong Tebal 14300 Malaysia Univ Tekn Malaysia Melaka Fak Teknol Kejuruteraan Elekt & Elekt Durian Tunggal 76100 Malaysia Univ Sains Malaysia Ctr Global Sustainabil Studies CGSS Hamzah Sendut Lib Level 5 Minden 11800 Malaysia Univ Pendidikan Sultan Idris Fac Art Comp & Creat Ind Tanjung Malim 35900 Malaysia

A segmentation process is usually required in order to analyze an image. One of the available segmentation approaches is by detecting the edges on the image. Up to now, there are many edge detection algorithms that researchers have proposed. Thus, the purpose of this systematic literature review is to investigate the available quality assessment methods that researchers have utilized to evaluate the performance of the edge detection algorithms. Due to the vast number of available literature in this area, we limit our search to only open-access publications. A systematic search in five publisher websites (i.e., IEEExplore, IET digital library, Wiley, MDPI, and Hindawi) and Scopus database was carried out to gather resources that are related to the edge detection algorithms. Seventy-three publications that are about developing or comparing edge detection algorithms have been chosen. From these publication samples, we have identified 17 quality assessment methods used by researchers. Among the popular quality assessment methods are visual inspection, processing time, confusion-matrix based measures, mean square error (MSE)-based measures, and figure of merit (FOM). This survey also indicates that although most of the researchers only use a small number of test images (i.e., less than 10 test images), there are available datasets with a larger number of images for digital image segmentation that researchers can utilize.

关键词： Image edge detection detection algorithms Quality assessment Systematics Bibliographies Image segmentation Digital images Digital image processing edge detection algorithm image segmentation assessment validation quality measures reviews

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A Survey on the detection algorithms for False Data Injection Attacks in Smart Grids

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IEEE TRANSACTIONS ON SMART GRID 2020年第3期11卷 2218-2234页

作者： Musleh, Ahmed S. Chen, Guo Dong, Zhao Yang Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia

Cyber-physical attacks are the main substantial threats facing the utilization and development of the various smart grid technologies. Among these attacks, false data injection attack represents a main category with its widely varied types and impacts that have been extensively reported recently. In addressing this threat, several detection algorithms have been developed in the last few years. These were either model-based or data-driven algorithms. This paper provides an intensive summary of these algorithms by categorizing them and elaborating on the pros and cons of each category. The paper starts by introducing the various cyber-physical attacks along with the main reported incidents in history. The significance and the impacts of the false data injection attacks are then reported. The concluding remarks present the main criteria that should be considered in developing future detection algorithms for the false data injection attacks.

关键词： Smart grids detection algorithms Explosions Security Pipelines Generators Malware Cyber-physical attacks data-driven detection algorithms false data injection machine learning model-based detection algorithms smart grid state estimation stealth attacks

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