现有线对象三角剖分算法没有顾及线对象的整体结构特征,导致三角剖分质量不高,难以支持大数据量的矢量制图和高更新率的动态制图。本文提出线对象的惯性函数,设计了一种线对象的单调分解与三角剖分方法。惯性函数的单调递增区间作为线对象的渐变区间,连续剖分为一个优化的三角形条带;惯性函数的单调递减区间作为线对象的突变区间,离散剖分为一个优化的三角形扇。试验表明:本文方法三角剖分的顶点、三角形、图元的个数均优于基于顶点和基于线段的三角剖分方法,能够显著提升线对象的绘制效率。本文方法也适用于封闭线型、宽度渐变线型与光滑线型。
Without taking polyline global structure into consideration, current polyline tessellation methods tend to make low quality decomposition. It makes them difficult to support vector mapping with large dataset and dynamic mapping with high update rate. This paper proposed a polyline momentum function and designed a monotone decomposition and tessellation method. The monotonous increasing intervals of the momentum function, as the gradient intervals of polyline, are divided continuously into optimized triangle strips. The monotone decreasing intervals of the momentum function, as the mutational intervals of polyline, are divided discretely into optimized triangle fans. The experiment results show that the decomposition quality measured by the numbers of triangulation vertices, triangles and primitives using this method are better than that based on vertex and line segment and can significantly improve the drawing efficiency for polyline. This method is also applicable to closed, width gradient and smooth line style.
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