基于聚类方法的对象阴影识别方法研究  

Clustering Based Object Shadow Recognition Algorithm

作　　者：张晓丹[1] 李春来[1] 金兆岩[2] 

机构地区：[1]吉首大学信息科学与工程学院,吉首416000 [2]国防科学技术大学计算机学院,长沙410073

出　　处：《计算机科学》2015年第9期309-312,共4页Computer Science

基　　金：湖南省自然科学基金资助项目(11JJ6065)资助

摘　　要：图像处理中的对象阴影计算影响着图像的渲染速度,是图像处理领域的重要研究内容。为了进一步提高对象阴影的渲染速度,提出了一种基于聚类方法的对象阴影识别方法。按照光线的衰减半径将光线表示为一个个球体,当球体之间的距离大于预定义的最小距离时,将其划分到两个不同的类中,采用自上而下的层次方法对光线进行聚类。在聚类过程中,光线的衰减半径随着与光源的距离呈线性增长。对光线进行聚类分析后,对同一聚类内的光线采用相同的渲染方式,因而提高了阴影的渲染效率。最后通过实验验证了提出的方法的有效性。Object shadow computation is a critical issue for object rendering in image processing,and thus it is an impor- tant research issue in image processing field. In order to further improve the efficiency of shadow rendering, this paper proposed a clustering based object shadow recognition algorithm. We represented each light as a sphere according to its attenuation range,classified lights into different classes while the distance between them extended the predefined mini- mum distance,and applied a top-down hierarchal clustering method for lights. During the process of clustering, the at- tenuation range of light increases linearly with the distance between light and the light source. After clustering the lights into different classes, we rendered lights of a class by the same texture, and thus, the efficiency of rendering shadow in an image is improved largely. Finally,we validated the efficiency of our algorithm according to some experiments.

关 键 词：对象渲染 阴影计算 聚类 图像处理 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]