Yuanjing Feng

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An important task in most 3D measurement systems based on machine vision is camera calibration, whose objective is to estimate the internal and external parameters of each camera. A new accurate calibration method with multilevel process of camera parameter is presented. Flexibly making use of geometry imaging theory, our algorithm obtain all the parameters(More)
PURPOSE Higher order tensor (HOT) imaging approaches based on the spherical deconvolution framework have attracted much interest for their effectiveness in estimating fiber orientation distribution (FOD). However, sparse regularization techniques are still needed to obtain stable FOD in solving the deconvolution problem, particularly in very high orders.(More)
A new DBSCAN clustering based niching GA (DCNGA) algorithm that used to locate all global optima in uneven multimodal domain is presented in the paper. In order to remove some a priori knowledge requirements of standard sharing, such as peaks number and sharing distance, DCNGA using DBSCAN clustering algorithm to identify the niche automatically, and(More)
Weights of edges and nodes on food webs which are available from the empirical data hide much information about energy flows and biomass distributions in ecosystem. We define a set of variables related to weights for each species i, including the throughflow T i , the total biomass X i , and the dissipated flow D i (output to the environment) to uncover the(More)
Level set methods are often used to solve the image segmentation problem. A new method based on momentum level set segmentation is applied to extract phase change line automatically from complex phase change thermography sequence. Firstly, effective phase change information is obtained by the inter-frame difference with the template image and the(More)
Diffusion-weighted magnetic resonance imaging is a non-invasive imaging method that has been increasingly used in neuroscience imaging over the last decade. Partial volume effects (PVEs) exist in sampling signal for many physical and actual reasons, which lead to inaccurate fiber imaging. We overcome the influence of PVEs by separating isotropic signal from(More)