Aero-optic effects cause distortions, including blurring, vibration, deformation and spatial shifting, of the objects in the image obtained by the infra-red sensor. Contributions of this paper are in the following two...
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In micromanipulation, the microscope vision servoing can achieve a high performance. In order to avoid the complicated calibration of intrinsic parameter of camera, We apply an improved broyden's method to estimat...
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Due to the thrive of networking multimedia, artificial intelligence and embedded system, video surveillance system is evolved from computer-based to embedded-based. This paper presents an intelligent multimedia survei...
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Due to the thrive of networking multimedia, artificial intelligence and embedded system, video surveillance system is evolved from computer-based to embedded-based. This paper presents an intelligent multimedia surveillance system based on embedded video server. Design and implementation issues of this surveillance system are discussed including system architecture, hardware design and software framework. Moreover, practical applications show that our framework can suitable for commercial applications.
The paper proposes a shape-adaptive wavelet coding algorithm for the known object of the diagnostic region of three-dimensional medical images. The new algorithm only applies to the shape-adaptive transformation of th...
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The paper proposes a shape-adaptive wavelet coding algorithm for the known object of the diagnostic region of three-dimensional medical images. The new algorithm only applies to the shape-adaptive transformation of the pixels inside the object for decorrelation. After transformation, the number of coefficients of the object is as many as that of the pixels inside the image area. To achieve a quick and lossless transformation, a novel shape-adaptive wavelet transform based on lifting scheme for arbitrarily shaped object is proposed. By analyzing the location of invalid coefficients transformed, the paper also proposes a modified OB-3DSPECK (Object-based Set Partitioned Embedded Block Coder) method that cancels symbol outputs of invalid block or coefficients outside the object, specifically, only two types of symbols are output to arithmetic coding codec. For the object region of three-dimensional medical images, the proposed algorithm supports the lossy-to-lossless embedded en/decoding. Experimental results show that the proposed algorithm outperforms OB-3DSPIHT by 0.5 dB on the average SNR. Furthermore, because of the reduction of the output of one type symbol, the arithmetic coding becomes optional.
In order to identify multi micro objects, an improved support vector machine algorithm is present, which employs invariant moments based edge extraction to obtain feature attribute and then presents a heuristic attrib...
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On visual tracking, a particle filter algorithm was presented to track a moving target under clutter environment which can deal with rotation, scale changes, variations in the light source and partial occlusions. So i...
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On visual tracking, a particle filter algorithm was presented to track a moving target under clutter environment which can deal with rotation, scale changes, variations in the light source and partial occlusions. So it can track the target with robustness. The proposed method was based on particle filter, integrated with color histogram in the measurement model, and the system model was second order autoregressive process. The algorithm took into account the latest observations and the tracked target can be rigid or non-rigid. Also the method can run in real-time. The experimental results confirm that the method is effective even when the monocular camera is moving and the target object is partially occluded in a clutter background.
This paper provided a mathematic model for Three Gorges-Gezhou dam co-scheduling problems, based on full analysis of Three Gorges-Gezhou dam's actual needs, to maximize the total throughput of Three Gorges-Gezhou ...
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This paper provided a mathematic model for Three Gorges-Gezhou dam co-scheduling problems, based on full analysis of Three Gorges-Gezhou dam's actual needs, to maximize the total throughput of Three Gorges-Gezhou dam, to maximize the utilization ratio of shiplock area and minimize the total navigation shiplock waiting time under eight constraint conditions. Then a scheduling algorithm based on GA was pointed out. The three gorges south lock, Gezhou dam lock, the three gorges north lock were optimization searched separately in the GA algorithm. The scheduling results of the three gorges south lock were taken as the origin of the whole plan period, and also were taken as the basis of the Gezhou dam scheduling together with the ship applied information. The scheduling results of Gezhou dam were regarded as the basis of the three gorges north lock scheduling together with the ship applied information, so repeated, until the optimal scheduling results were given, or the most iterative step was reached. The applied result shows that making a period plan of two dam five lock only needs 2 minutes, and the plan is quite effective according to practical application.
This paper presents a sliding-mode-based diagonal recurrent cerebellar model articulation controller (SDRCMAC) for multiple-input-multiple-output (MIMO) uncertain nonlinear systems. Sliding mode technology is used to ...
This paper presents a sliding-mode-based diagonal recurrent cerebellar model articulation controller (SDRCMAC) for multiple-input-multiple-output (MIMO) uncertain nonlinear systems. Sliding mode technology is used to reduce the dimension of the control system. Two learning stages are adopted to train the SDRCMAC and to improve the stability of the control system. Lyapunov stability theorem and Barbalat's lemma are adopted to guarantee the asymptotical stability of the system. Performance is illustrated on a two-link robotic control and motor control of the human arm in the sagittal plane.
Multiobjective evolutionary clustering approach has been successfully utilized in data clustering. In this paper, we propose a novel unsupervised machine learning algorithm namely multiobjective evolutionary clusterin...
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Multiobjective evolutionary clustering approach has been successfully utilized in data clustering. In this paper, we propose a novel unsupervised machine learning algorithm namely multiobjective evolutionary clustering ensemble algorithm (MECEA) to perform the texture image segmentation. MECEA comprises two main phases. In the first phase, MECEA uses a multiobjective evolutionary clustering algorithm to optimize two complementary clustering objectives: one based on compactness in the same cluster, and the other based on connectedness of different clusters. The output of the first phase is a set of Pareto solutions, which correspond to different tradeoffs between two clustering objectives, and different numbers of clusters. In the second phase, we make use of the meta-clustering algorithm (MCLA) to combine all the Pareto solutions to get the final segmentation. The segmentation results are evaluated by comparing with three known algorithms: K-means, fuzzy K-means (FCM), and evolutionary clustering algorithm (ECA). It is shown that MECEA is an adaptive clustering algorithm, which outperforms the three algorithms in the experiments we carried out.
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