基于工业CT图像重构的网格模型的全局优化方法

针对用工业CT切片图像直接重构得到的网格模型质量不高的问题,提出一种不受拓扑结构限制的隐式曲面重构全局优化方法。该方法将三维表面模型用隐式函数来表示,通过模型提供的点云信息计算出隐式函数,提取等值面,实现曲面重构。针对隐式曲面重构数据处理量大的问题,引入FFTW快速傅里叶变换来提高效率。实验结果表明,该方法能够同时实现三角网格模型的去噪、网格平滑、简化以及孔洞修补,与保特征的均匀化网格平滑算法相比,去噪效果更好,效率更高。

Global optimization for mesh model reconstructed by industrial CT serial images

The quality of the mesh model is poor by direct-reconstruction from the industrial CT slice images. This paper proposed a global optimization methods based on implicit surface reconstruction without topology restrictions. In this method, 3D surface model was represented by an implicit function, which was calculated first using point cloud information provided by the model, then iso-surface extraction was employed. As for the large data processing problems, we used the fast Fourier transform to improve the efficiency of the algorithm. Experimental results showed that our algorithm could realize mesh denoising, simplifying, smoothing and hole-filling at one time. Compared with the feature-preserving uniform mesh smoothing algorithm, the presented algorithm could effectively remove noise from meshes within a short time.