A Multisource Contour Matching Method Considering the Similarity of Geometric Features

The existing multi-source contour matching studies have focused on the matching methods with consideration of topological relations and similarity measurement based on spatial Euclidean distance,while it is lack of taking the contour geometric features into account,which may lead to mismatching in map boundaries and areas with intensive contours or extreme terrain changes.In light of this,it is put forward that a matching strategy from coarse to precious based on the contour geometric features.The proposed matching strategy can be described as follows.Firstly,the point sequence is converted to feature sequence according to a feature descriptive function based on curvature and angle of normal vector.Then the level of similarity among multi-source contours is calculated by using the longest common subsequence solution.Accordingly,the identical contours could be matched based on the above calculated results.In the experiment for the proposed method,the reliability and efficiency of the matching method are verified using simulative datasets and real datasets respectively.It has been proved that the proposed contour matching strategy has a high matching precision and good applicability.

Contour Matching Using Wavelet Transform and Multigrid Methods

In this paper, wavelet transform and multigrid method are combined to make the method more practical. It is known that Gaussian filtering causes shrinkage of data. To overcome this disadvantage, Gaussian filtering is replaced with wavelet transform. This method introduces no curve shrinkage. Then, the linearized form of objective equation is proposed. This makes contour matching easier to implement. Finally, the multigrid method is used to speed up the convergence.

3D reconstruction method based on contour features

To guarantee the accuracy and real-time of the 3D reconstruction method for outdoor scene,an algorithm based on region segmentation and matching was proposed.Firstly,on the basis of morphological gradient information,obtained by comparing color weight gradient images and proposing a multi-threshold segmentation,scene contour features were extracted by a watershed algorithm and a fuzzy c-means clustering algorithm.Secondly,to reduce the search area,increase the correct matching ratio and accelerate the matching speed,the region constraint was established according to a region＇s local position,area and gray characteristics,the edge pixel constraint was established according to the epipolar constraint and the continuity constraint.Finally,by using the stereo matching edge pixel pairs,their 3D coordinates were estimated according to the binocular stereo vision imaging model.Experimental results show that the proposed method can yield a high stereo matching ratio and reconstruct a 3D scene quickly and efficiently.

Object detection based on combination of local and spatial information

A method of object detection based on combination of local and spatial information is proposed. Firstly, the categorygiven representative images are chosen through clustering to be templates, and the local and spatial information of template are ex- tracted and generalized as the template feature. At the same time, the codebook dictionary of local contour is also built up. Secondly, based on the codebook dictionary, sliding-window mechanism and the vote algorithm are used to select initial candidate object win- dows. Lastly, the final object windows are got from initial candidate windows based on local and spatial structure feature matching. Experimental results demonstrate that the proposed approach is able to consistently identify and accurately detect the objects with better performance than the existing methods.

Spin-dependent thermoelectric effect and spin battery mechanism in triple quantum dots with Rashba spin-orbital interaction

We have studied spin-dependent thermoelectric transport through parallel triple quantum dots with Rashba spinorbital interaction（RSOI） embedded in an Aharonov-Bohm interferometer connected symmetrically to leads using nonequilibrium Green＇s function method in the linear response regime.Under the appropriate configuration of magnetic flux phase and RSOI phase,the spin figure of merit can be enhanced and is even larger than the charge figure of merit.In particular,the charge and spin thermopowers as functions of both the magnetic flux phase and the RSOI phase present quadruple-peak structures in the contour graphs.For some specific configuration of the two phases,the device can provide a mechanism that converts heat into a spin voltage when the charge thermopower vanishes while the spin thermopower is not zero,which is useful in realizing the thermal spin battery and inducing a pure spin current in the device.

Simulation research on a minimum root-mean-square error rotation-fitting algorithm for gravity matching navigation

Gravity/inertial combination navigation is a leading issue in realizing passive navigation onboard a submarine. A new rotation-fitting gravity matching algorithm, based on the Terrain Contour Matching (TERCOM) algorithm, is proposed in this paper. The algorithm is based on the principle of least mean-square-error criterion, and searches for a certain matched trajectory that runs parallel to a trace indicated by an inertial navigation system on a gravity base map. A rotation is then made clockwise or counterclockwise through a certain angle around the matched trajectory to look for an optimal matched trajectory within a certain angle span range, and through weighted fitting with another eight suboptimal matched trajectories, the endpoint of the fitted trajectory is considered the optimal matched position. In analysis of the algorithm reliability and matching error, the results from simulation indicate that the optimal position can be obtained effectively in real time, and the positioning accuracy improves by 35% and up to 1.05 nautical miles using the proposed algorithm compared with using the widely employed TERCOM and SITAN methods. Current gravity-aided navigation can benefit from implementation of this new algorithm in terms of better reliability and positioning accuracy.

Terrain matching localization for hybrid underwater vehicle in the Challenger Deep of the Mariana Trench

The maximum ocean depth so far reported is about 11000 m,and is located in the Mariana Trench in the Western Pacific Ocean.The hybrid unmanned underwater vehicle,Haidou,is developed to perform scientific survey at the deepest parts of the Earth oceans.For vehicles working at the full-ocean depth,acoustic positioning is the most effective and popular method.The 11000 m class acoustic positioning system is relatively massive and complex,and it requires specialized research vessels equipped with compatible acoustic instruments.As a compact testbed platform,it is impractical for Haidou to carry an LBL/USBL beacon with its large volume and weight.During the descent to about 11000 m,horizontal drift could not be eliminated because of the hydrodynamics and uncertain ocean currents in the sea trials.The maximum depth recorded by Haidou is 10905 m,and determining the precise location of the deepest point is challenging.With the bathymetric map produced by a multibeam sonar,the terrain contour matching(TERCOM)method is adopted for terrain matching localization.TERCOM is stable in providing an accurate position because of its insensitivity to the initial position errors.The final matching results show the best estimate of location in the reference terrain map.