具有时间约束层流特征的美术图形符号化设计

Symbolic Design of Art Graphics with Time Constraint Laminar Characteristics

为了解决美术图形符号化过程中RLA(Random Laplace Algorithm)算法对其时间约束信息描述不完整的问题,提出了一种具有时间约束层流特征的美术图形符号化算法(Time constraint laminar characteristics,缩写为TCLC算法).该算法将时间约束符号视为矢量,将两个时间约束层流特征分量引入其中,使得原来的RLA符号进行转换,得到矢量符号,此时对于其均值水平以及发散程度的描述,可通过时间约束均值与方差进行描述.由于该算法能够比RLA提供更多的描述信息,因而在流数据设计应用中能够获得比RLA更精确的结果.大量的实验也证实了它的出色表现.

In order to overcome the incomplete description of time constraint information in art graphics symbolization by using the Random Laplace algorithm （ RLA ） , The time constraint laminar characteristics （TCLC） is proposed in this paper. In the proposed algorithm, the time constraint symbol is considered as a vector, and the two time constrained laminar characteristic components are introduced into it, so that the original RLA symbols are converted to get the vector symbols. At this time, the mean level and the degree of divergence can be described by the mean of time constraint and the variance. Because this algorithm can provide more information than RLA, it can get more accurate results than RLA in streaming data design application. A large number of experiments also confirmed its excellent performance.