快速Arclet变换及其在工业CT图像圆测量中的应用

Fast Arclet transform and its application in circle measurement of industrial CT images

为了准确描述工业CT图像中的圆形结构,提出一种基于多尺度几何分析工具Arclet的圆测量算法。首先,通过分析单尺度Arclet基函数间的空间关系,设计了单尺度快速Arclet数字变换算法;基于该Arclet数字变换,提取出单尺度上的候选圆特征。然后,考虑Arclet相邻尺度基函数间的空间关系并结合多尺度四叉树结构,按照从根到叶的方向,依次对相邻尺度间的候选圆特征进行取舍。最后,融合各尺度剩余的候选圆特征,得到提取结果,并根据提取结果计算出半径等圆参数。基于实际工业CT图像进行了圆测量试验,结果表明,最大半径绝对误差的绝对值<0.1mm,最大半径相对误差的绝对值<0.5%;即使对原工业CT图像引入不同强度的高斯噪声,测量结果依然满足要求。本文提出的工业CT图像圆测量算法对噪声干扰具有很好的抑制能力,能满足准确描述工业CT图像中圆形结构的要求。

To accurately describe the circular structures of industrial CT images,a measurement algorithm based on multi-scale geometric analysis tool,named Arclet,was presented.Firstly,a fast mono-scale Arclet numeric transform algorithm was designed through analysis of the spatial relationship between mono-scale Arclet basis functions.Then,the candidate circular features at mono-scale were extracted based on the mono-scale numeric transform transform.By considering the spatial relationship between Arclet basis functions at adjacent scales and the multi-scale tree structure,the candidate circular features between adjacent scales were chosen from a root to leafs.Finally,the surplus circular feature of each scale was fused to obtain the extracted results,and to calculate the related parameters such as radius based on the extracted results.The circle measurement for an actual industrial CT image was performed and the measurement results show that the absolute value of maximum radius absolute error is less than 0.1mm and that of maximum radius relative error is less than 5%.Evenif adding the Gauss noise of different intensities into the original industrial CT image,the measurement results are still can meet the requirements.The measurement algorithm based on fast Arclet transform has better ability to inhibit the noise interference and meet the requirements of industrial CT images for circular structure description.