Mosaic Image Generation Method Based on Geodesic Voronoi Diagram

马赛克是一种非真实感的渲染效果，源图像被不同颜色、形状的嵌片组合而成。本文提出一种基于测地距离度量下的保持源图像特征信息的自适应马赛克图像生成方法。我们方法结合了测地距离度量和重心Voronoi图方法。测地距离度量是由源图像的特征曲线定义，特征曲线是利用特征算子从源图像中自动提取得到。Voronoi图在该测地距离度量下使用快速行进算法生成，这样可以保证生成的Voronoi图的Voronoi多边形边界与特征曲线重合，从而保持输入源图像的特征信息。除了测地距离度量外我们还定义了马赛克图像的密度函数。密度函数通过一个距离场定义，它表示每个像素点到源图像特征曲线的最短距离，可以通过欧氏距离变换快速计算...Mosaic is a non-photorealistic rendering method,which synthesizes a large image by packing a collection of small colored tiles. This thesis presents a novel feature-preserving method for mosaic image generation,which is based on Voronoi diagram under a non-Euclidean metric. Each Voronoi cell is taken as a tile in the mosaic image. We combine the geodesic distance and centroidalVoronoi diagram.The ...学位：工学硕士院系专业：信息科学与技术学院_计算机应用技术学号：2302011115445

Adaptive Knot Placement in Non-uniform B-spline Surface Fitting

针对非均匀b样条的节点设置问题,提出一种利用非均匀b样条曲面拟合离散数据的迭代算法,通过优化节点分布来改进拟合曲面的质量.该算法以带参数化的三角网格曲面为输入,在首次迭代中根据输入曲面的几何特征将其对应的参数域划分成若干个子区域,并使得每个子区域上累积的几何特征信息量近似相等,子区域的重心坐标将取为首次迭代的节点;在随后的迭代中,保证前次迭代生成的重心位置固定不变,并根据前次迭代得到的曲面拟合误差再次将区域划分成累积误差接近相等的子区域,新增加的子区域重心的坐标选为拟加入的节点.文中算法自适应地在曲面形状复杂或拟合误差大的区域引入更多的控制顶点,使得拟合曲面的质量得以逐步改进.实验结果表明,该算法快速有效,在拟合具有明显几何特征的输入数据时具有优势.Knot placement of non-uniform B-spline is studied, and an iterative surface fitting scheme is proposed by exploring the degrees of freedom of knots to improve the fitting surface's quality.Our algorithm takes as input triangular meshes with parameterization.In the first iteration, the parametric domain is partitioned into several sub-regions with equally accumulated surface geometric information, and the coordinates of the centroids are chosen as the candidates of knots; in the following iteration steps, we partition the regions according to the fitting errors analogously while the centroids generated by previous steps remain unchanged.The fitting surface's quality is progressively improved as more control points are adaptively introduced into the region of the surface with more features or larger fitting error.Several experiments demonstrate the efficacy of our method in fitting surface with distinct geometric features.国家自然科学基金(61100105;61100107;61170324;61272300); 福建省自然科学基金(2011J05007;2012J01291

Feature-Preserving Method for Mosaic Image Generation

马赛克图像是一种非真实感的渲染效果,主要通过组合不同形状、颜色的嵌片合成目标图像.基于测地距离度量下的VOrOnOI图结构,提出一种保特征的自适应马赛克图像生成方法.首先利用特征算子自动提取出源图像中的特征线,并根据这些特征线定义测地度量,从而保证在测地度量下生成的VOrOnOI图的边和图像特征边重合;然后通过距离变换计算每个像素到图像特征线的最近距离,并利用该距离场定义马赛克图像的密度函数;最后结合重心VOrOnOI图理论,采用llOyd迭代算法优化嵌片的形状,得到最终的马赛克图像.实验结果表明,该方法得到的马赛克效果图有效地保持了源图像特征,疏密程度自适应、连续过渡,嵌片形状规则、排列整齐.Mosaic is a non-photorealistic rendering method,which synthesizes a large image by packing a collection of small colored tiles.This paper presents a novel feature-preserving method for mosaic image generation,which is based on Voronoi diagram under a non-Euclidean metric.Each Voronoi cell is taken as a tile in the mosaic image.The feature edges are first extracted from the input image automatically.Then a metric matrix is defined such that the edges of the Voronoi diagram under the new metric align with the feature edges.The sizes of the Voronoi cells are controlled by a density function derived from a distance transformation.Finally,the shapes of the Voronoi cells are further optimized by Lloyd's method.Experimental results show that,our algorithm keeps the features of the input image faithfully.The tiles in the generated mosaic image are well shaped and arranged,and vary in size according to the density function.国家自然科学基金(61100107;61100105); 福建省自然科学基金(2011J05007;2012J01291