Traffic flow detection plays an important role in intelligent Transportation Systems(ITS).Video based traffic flow detection system is the most widely used strategy in *** this circumstance,we design and implement a v...
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ISBN:
(纸本)9781457718342
Traffic flow detection plays an important role in intelligent Transportation Systems(ITS).Video based traffic flow detection system is the most widely used strategy in *** this circumstance,we design and implement a video based traffic flow detection system which is called MyTD in this *** takes advantages of both shadow removal and optical flow ***,we introduce the current development of ITS and focus on the video based traffic detection technology,which is the key to ***,a shadow removal algorithm combining information in both RGB and HSV color spaces is ***,based on the Iterative Pyramidal LK Optical Flow Algorithm,a vehicle tracking function is realized by OpenCV,as well as a Connected Components Labeling function and the vehicle counting ***,MyTD is implemented and tested based on the algorithm presented *** results show the outstanding performance of our method comparing with traditional optical flow algorithms.
Considering the shortage of edge preservation and low direction-resolution for SAR image segmentation based on the conventional wavelet transform domain, a new segmentation method is proposed based on Gray-Level Coocc...
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Considering the shortage of edge preservation and low direction-resolution for SAR image segmentation based on the conventional wavelet transform domain, a new segmentation method is proposed based on Gray-Level Cooccurrence Probability (GLCP) features in the overcomplete Brushlet domain. This method compresses the redundant GLCP features extracted by the adaptive window Gabor filtering in different direction coefficient blocks using compressed sensing, then the Fuzzy C-Mean (FCM) clustering method is utilized to complete the clustering and obtain the segmentation result. The experiment results show that the new method has advantages in the edge preservation and direction extraction, and obtains better segmentation results with respect to other methods.
As we know, a novel adaptive visual servoing strategy has been proposed for the control of robot manipulators with an eye-in-hand configuration, where an adaptive law is used to estimate the unknown parameters determi...
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Traditional image matching algorithm based on gray correlation provides accurate results but it is time-consuming because of large amount of calculation. An improved gray correlation based image matching algorithm bas...
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In this paper, a third-order canonical circuit with a memristor is investigated. Unlike the conventional circuit systems, it has an equilibrium set, whose stability is affected by the initial state of the memristor. T...
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Nonnegative matrix factorization (NMF) is an increasingly popular technique for data processing and analysis. For an incomplete data matrix, the weighted nonnegative matrix factorization (WNMF) is employed to decompos...
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Nonnegative matrix factorization (NMF) is an increasingly popular technique for data processing and analysis. For an incomplete data matrix, the weighted nonnegative matrix factorization (WNMF) is employed to decompose it. But the searching step size in WNMF is not optimal along the given searching direction. This paper studies the incomplete nonnegative matrix factorization (INMF) and proposes an accelerated algorithm. First, INMF is transformed into solving alternatively two nonnegative least squares (NNLS) problems. For each NNLS problem, the exact step size is chosen along the searching direction. Then, the complexity of NNLS problems is analyzed. Finally, experimental results show that the proposed method outperforms WNMF.
With the wide use of power conversion devices, harmonic currents are being injected into the power grid. Shunt Active Power Filters (SAPF) is a power electronic device to compensate the harmonic currents caused by non...
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Memristor has received significant attentions since Strukov et al released their invention on April 30, 2008 at Nature Letters. Based on the model of Strukov et al, analytic expression of the internal state is obtaine...
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The global asymptotic stability of fuzzy cellular neural networks with unbounded time-varying delays and Lipschitz continuous activation functions is investigated in this brief. Based on the concept of comparison, som...
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Many real world problems involve the simultaneous optimization of various and often conflicting objectives. These optimization problems are known as multi-objective optimization problems. Evolutionary multi-objective ...
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Many real world problems involve the simultaneous optimization of various and often conflicting objectives. These optimization problems are known as multi-objective optimization problems. Evolutionary multi-objective optimization, whose main task is to deal with multi-objective optimization problems by evolutionary computation techniques, has become a hot topic in evolutionary computation community. The solution diversity of multi-objective optimization problems mainly focuses on two aspects, breadth and uniformity. After analyzing the traditional methods which were used to maintain the diversity of individual in multi-objective evolutionary algorithms, a novel nondominated individual selection strategy based on adaptive partition is proposed. The new strategy partitions the current trade-off front adaptively according to the individual's similarity. Then one representative individual will be selected in each partitioned regions for pruning nondominated individuals. For maintaining the diversity of the solutions, the adaptive partition selection strategy can be incorporated in multi-objective evolutionary algorithms without the need of any parameter setting, and can be applied in either the parameter or objective domain depending on the nature of the problem involved. In order to evaluate the validity of the new strategy, we apply it into two state-of-the-art multi-objective evolutionary algorithms. The experimental results based on thirteen benchmark problems show that the new strategy improves the performance obviously in terms of breadth and uniformity of nondominated solutions.
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