Using a heuristic approach, the performance of the self-synchronized decision-directed maximum-likelihood (ML) feedforward (FF) carrier phase error detection (PED) algorithm has been optimized. Compared to the origina...
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Using a heuristic approach, the performance of the self-synchronized decision-directed maximum-likelihood (ML) feedforward (FF) carrier phase error detection (PED) algorithm has been optimized. Compared to the original algorithm, it has been shown that for uncoded single channel (O)QPSK modems the optimized algorithm has a better phase error variance at low to medium signal to noise ratio (SNR). Further simulations have shown that the noise performance of the optimized algorithm at medium to high SNRs is superior to that of some well-known algorithms; the noise performance approaches the Cramer-Rao bound (CRB). This proves that the optimized algorithm has less tracking jitter at medium to high SNR which is a desirable feature in improving the BER performance.
A major issue for video surveillance embedded systems is the need to continuously perform a number of highly demanding operations even when the analyzed scene does not show peculiar or interesting features, so that po...
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A major issue for video surveillance embedded systems is the need to continuously perform a number of highly demanding operations even when the analyzed scene does not show peculiar or interesting features, so that power consumption is a critical issue. In this paper we present a low-power multimodal embedded video surveillance system aimed at detecting objects abandoned/removed in/from a static monitored scene. Energy-awareness is achieved by means of an efficient and scalable objects abandon/removal detection algorithm, a Linux governor that controls CPU frequency and operating mode so as to establish an optimal trade-off between fulfilling the application efficiency-accuracy requirements and maximizing battery life and, finally, a pyroelectric infrared sensor that allows to wake up the CPU only when video processing is actually needed.
Real-time video transmission is considered as an important means for information distribution. One major application of it is e-learning, which requires real-time video processing and transmission. On the other hand, ...
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ISBN:
(纸本)9781424407781;1424407796
Real-time video transmission is considered as an important means for information distribution. One major application of it is e-learning, which requires real-time video processing and transmission. On the other hand, the process of cut detection is a fundamental component in automatic video browsing, indexing, searching, retrieval, and archiving. This paper introduces a new video cut detection technique that uses dominant lines and angles extracted from edge information of the video contents. To the best of our knowledge, it is the first works done for cut detection in e-learning application. This method is compatible with our applicationpsilas requirements and has a low complexity and high speed. We have compared the performance of our proposed method against three established techniques and have evaluated the results using different video sequences.
Ship detection in polarimetric SAR images of non-homogeneous sea areas is considered. We demonstrate the impact of non-homogeneous sea features on the false alarm rate and the need of extracting the image structure. W...
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Ship detection in polarimetric SAR images of non-homogeneous sea areas is considered. We demonstrate the impact of non-homogeneous sea features on the false alarm rate and the need of extracting the image structure. We thus introduce polarimetric segmentation procedures that cooperate with high-resolution polarimetric detection features for the control of the false alarms. Different polarimetric segmentation-plus-detection procedures are tested over real data to devise the appropriate method to exploit the polarimetric information.
作者:
J. IngladaCNES
CNES French Space Agency DSO/OT/QTIS Toulouse France
Presents a method for performing change detection using a pair of SAR images acquired at different dates. The main difficulty with SAR images is the presence of speckle noise which may produce noisy change images if t...
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Presents a method for performing change detection using a pair of SAR images acquired at different dates. The main difficulty with SAR images is the presence of speckle noise which may produce noisy change images if they are acquired with slightly different angles. The technique proposed in the present paper uses a parametric estimation of the probability distributions locally in each image as a characterization of the surfaces. The change is measured as a distance between these probability laws. The dissimilarity measure between the statistical distributions used here is a symmetric version of the Kullback-Leibler divergence.
Bases on present harmonic detection algorithms, single-phase load current is decomposed and a novel single-phase current detection algorithm, which is simple, reliable, response quickly and favors the hardware realiza...
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Bases on present harmonic detection algorithms, single-phase load current is decomposed and a novel single-phase current detection algorithm, which is simple, reliable, response quickly and favors the hardware realization, is proposed, in order to solve complexity of algorithm and slow response of common used single-phase harmonic detection methods. Meanwhile, as the method need to use low pass filter, an improved method is is analysed. By increasing time delay unit, the effect of 2nd harmonic was eliminated, and the cut-off frequency of the low-pass filter was increased without adding the filter order. The response time of improved detection was shorten about half period. Correctness and validity of the proposed method were verified through simulating and experiment.
In recent years, the DDoS (Distributed Denial of Service) attack continues to be one of the most dangerous threats even in the SDN (Software Defined Networking) environment. Many approaches have been proposed to deal ...
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ISBN:
(数字)9781665423182
ISBN:
(纸本)9781665446198
In recent years, the DDoS (Distributed Denial of Service) attack continues to be one of the most dangerous threats even in the SDN (Software Defined Networking) environment. Many approaches have been proposed to deal with the DDoS attacks in the SDN environment. Among those approaches, the two-step detection, in which a trigger mechanism is added before the detection algorithm is called, is gaining more and more attention. In other words, it is the trigger, not the resource-consuming detection algorithm, that constantly monitors network traffic. Thus, the detection algorithm is only called when it is triggered. However, in the existing two-step methods, the trigger uses a static threshold to determine whether or not to start the detection process. In practice, it is difficult to determine an appropriate threshold, and the threshold has a decisive effect on the frequency of the detection process being called and ultimately, it impacts detection performance. In this paper, we propose a self-feedback dynamic thresholding system in which the threshold used in the trigger is dynamically adjusted based on the previous results of trigger and detection. Experimental results and our discussion show that our proposal significantly reduces the number of calls to the resource-consuming detection algorithm with no sacrifice of detection result.
In steel manufacturing industry, as many advanced technologies increase manufacturing speed, fast and exact products inspection gets more important. This paper deals with a real-time defect detection algorithm for hig...
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In steel manufacturing industry, as many advanced technologies increase manufacturing speed, fast and exact products inspection gets more important. This paper deals with a real-time defect detection algorithm for high-speed steel bar in coil (BIC). To get good performance, this algorithm has to solve several difficult problems such as cylindrical shape of a BIC, influence of light, many kinds of defects. Additionally, it should process quickly the large volumes of image for real-time processing since a steel bar moves at high speed. Therefore defect detection algorithm should satisfy two conflicting requirements of reducing the processing time and improving the efficiency of defect detection. This paper proposes an effective real-time defect detection algorithm that can solve above problems. And the algorithm is implemented by a high speed image processing system and will be applied to a practical manufacturing line. Finally, the performance of the proposed algorithm is demonstrated by experiment results
Power theft detection has been a difficult issue for a long time, as part of the construction of the smart grid operation and maintenance management system (SOMS) of power facilities of village and town power supply s...
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Power theft detection has been a difficult issue for a long time, as part of the construction of the smart grid operation and maintenance management system (SOMS) of power facilities of village and town power supply stations (VTPS), a new algorithm based on user's electricity usage is proposed in this study. First, the regular curves of user power usage are computed and categorized based on the k-means clustering algorithm, then the Fréchet distance algorithm is used to calculate the discrepancies between the categorized curves and the target curve to identify suspicious users. Experiments shows the accuracy is 88.9%, which is a promising result.
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