A new method dealing with recognition of partially occluded and affine distortion objects is presented. The method is designed for objects with smooth curved boundary. It divides an object into affine-invariant parts ...
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A new method dealing with recognition of partially occluded and affine distortion objects is presented. The method is designed for objects with smooth curved boundary. It divides an object into affine-invariant parts based on the feature point. And a new approach for matching each part is presented in this paper. Robust Hausdorff distance (RHD) is introduced to measure the similarity between feature points set of model and that of target. In terms of the new RHD, the optimal affine transform can be estimated. And then the sub-curve match pairs are calculated based on the optimal affine transformation. The experimental results show proposed algorithm are capable of coping with partial occlusion and affine transformation.
In view of the problem that the global optical flow algorithm cannot acquire accurate motion parameter estimation at a low-gradient value, an improved method has been presented in order to enhance the self-adaptive ab...
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DNA sequence homology is a critical and fundamental problem in bioinformatics. In this paper, we solve this problem by use of the second order Markov modal instead of traditional sequence alignment because DNA charact...
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Aiming at the adverse effects on state estimation precision caused by measurement system error, a novel joint estimation algorithm of system error and state is proposed in this paper. In the new algorithm, combined wi...
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At present, in the field of pixel-level image fusion, researchers tend to treat each pixel independently, which destroys the relationship between the images to be fused. In view of this defects, this paper aims to pro...
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The aim of this work is to propose the fully automated pathological area extraction from multi-parametric 2D MR images of brain. The proposed method is based on multi-resolution symmetry analysis and automatic thresho...
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Based on the thought of ensemble forecast, Ensemble Kalman filter (EnKF) gives a typical implementation of Bayesian estimation in Monte-Carlo simulation. However, the sampling process of particles excessively relies o...
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Based on the thought of ensemble forecast, Ensemble Kalman filter (EnKF) gives a typical implementation of Bayesian estimation in Monte-Carlo simulation. However, the sampling process of particles excessively relies on the priori modeling information form the system state transition in EnKF, which inevitably causes the particle degeneracy phenomenon. In this paper, we propose a novel Ensemble Kalman filtering algorithm based on weights optimization of sampling particles. Firstly, combining with the importance-sampling technique, the contribution degree of state estimation from particles is effectively measured. Secondly, by increasing particles numbers with high weights and decreasing particles numbers with low weights, the sampling particles set is optimized in the global sense. In addition, the estimated method of importance weights on the basis of virtual observation is constructed in the framework of EnKF, and the adverse effects on the reliability and stability of particle weights caused by the observation random noise are improved. The experimental results show the feasibility and efficiency of the proposed algorithm.
A vertex separator in an undirected graph is a subset of the vertices, whose removal disconnects the graph in at least two nonempty connected components. Given a connected undirected graph G = (V ,E) with |V| = n, an ...
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In this paper, we present a new speech enhancement method based on robust principal component analysis. In the proposed method, noisy signal is transformed into time-frequency domain where background noise is assumed ...
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This paper introduces the theory of ϕ-Jensen variance. Our main motivation is to extend the connotation of the analysis of variance and facilitate its applications in probability, statistics and higher education. To t...
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