计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (22): 135-137.DOI: 10.3778/j.issn.1002-8331.2009.22.044

• 图形、图像、模式识别 • 上一篇    下一篇

建立在图像识别基础上的体绘制加速方法

何元烈1,陈 萍2,战荫伟1,陈仰纯2   

  1. 1.广东工业大学 计算机学院,广州 510006
    2.广州医学院 第一附属医院核医学科,广州 510120
  • 收稿日期:2009-03-03 修回日期:2009-04-27 出版日期:2009-08-01 发布日期:2009-08-01
  • 通讯作者: 何元烈

Volume rendering accelerating method based on image recognition

HE Yuan-lie1,CHEN Ping2,ZHAN Yin-wei1,CHEN Yang-chun2   

  1. 1.Faculty of Computer,Guangdong University of Technology,Guangzhou 510006,China
    2.The First Affiliated Hospital of Guangzhou Medical College,Guangzhou 510120,China
  • Received:2009-03-03 Revised:2009-04-27 Online:2009-08-01 Published:2009-08-01
  • Contact: HE Yuan-lie

摘要: 提出了一种新算法——IRVR(Image Recognition Volume Rendering),该算法能大幅降低冗余数据,从而提升体绘制速度。IRVR算法首先利用交叉熵阈值分割法从三维数据集中将物体像素和背景像素识别出来,然后将迭代光线追踪方法和物体检测采样策略结合起来对原始三维数据集进行采样。接着运用快速迭代法对分类数据集进行采样,从而定位视线与原始数据集的交点。IRVR算法还应用了准确正规采样方法(例如,三线性插值、样条插值等)在体绘制过程中对原始数据集进行插值。经过实验得出的结论证明IRVR算法既能提高体绘制的速度,又可以保证体绘制图像的质量。

关键词: 光线投射, 体绘制, 最小交叉熵, 图像识别

Abstract: A new algorithm(Image Recognition Volume Rendering,IRVR) is developed in this paper,which can remarkably decrease the redundant data during volume rendering.The IRVR algorithm uses the minimun cross-entropy threshold selection method to detecte the object and background voxels from a three dimensional dataset.An iterating ray tracing method combined with the objects detection sampling strategy is developed to sample the original dataset.The fast iterative method is implemented to sampling the classification dataset for locating the intersection position of the viewing ray and the original dataset.And the precise normal sampling method(for example,trilinear interpolation,spline interpolation,etc.) is applied to extract the gray value from the original dataset for volume rendering.The experiment result is given in this paper.It proves that the IRVR algorithm can improve the volume rendering speed and guarantee the quality of the volume rendering results.

Key words: ray casting, volume rendering, minimun cross-entropy, image recognition