文献类型：期刊文献

中文题名：采用3D Gaussian Facet模型的亚体素表面检测

英文题名：Surface Detection with Subvoxel Accuracy Using 3D Gaussian Facet Model

作者：王凯[1];张定华[1];刘晶[2];张顺利[1];赵歆波[1]

机构：[1]西北工业大学现代设计与集成制造技术教育部重点实验室,西安710072;[2]华东理工大学机械与动力工程学院,上海200237

年份：2007

卷号：19

期号：9

起止页码：1100

中文期刊名：计算机辅助设计与图形学学报

外文期刊名：Journal of Computer-Aided Design & Computer Graphics

收录：CSTPCD;;EI(收录号：20074210875788);Scopus;北大核心:【北大核心2004】；CSCD:【CSCD2011_2012】；

基金：国家自然科学基金(50375126);国家"十一五"科技支撑计划重点项目(2006BAF04B02);航空科学基金(04I53069).

语种：中文

中文关键词：工业CT;表面检测;亚体素;Gaussian;facet模型;矩

外文关键词：industrial computer tomography; surface detection; subvoxel accuracy; Gaussian facet model; moment

摘要：提出一种基于Gaussian facet模型的3D边缘检测算法.首先利用Gaussian加权最小二乘拟合,引入空间权因子表达图像采样点对模型参数估计的相对重要度,扩展了经典Haralick facet模型,建立了3D Gaussian facet模型及其计算公式;然后采用抗噪性好的3DIDDG算子估计梯度方向,并在该梯度方向上计算二阶方向导数过零点,以获得表面点亚体素位置.实验结果表明,该算法能有效地降低邻近边缘干涉对检测结果的影响,可更好地提取尺寸较小的结构边缘.
This paper presents a 3D edge detection algorithm based on Gaussian facet model. First we generalize the classic Haralick facet model and introduce the 3D Gaussian facet model using the Gaussian weighted least squares fitting, which uses spatial weights to express the relative importance of image samples in estimating model parameters. Then we employ the 3D integrated directional derivative gradient （IDDG） operator to robustly estimate the gradient direction, and along this direction the zeros of the second directional derivatives are computed to locate the subvoxel positions of the surface points. Experimental results show our method can effectively reduce the interference of adjacent edge and can achieve good performance in extracting edge points of small structures.