Elongated anisotropic Gaussian filters are used for the orientation estimation of fibers. In cases where computed tomography images are noisy, roughly resolved, and of low contrast, they are the method of choice even if being efficient only in virtual 2D slices. However, minor inaccuracies in the anisotropic Gaussian filters can carry over to the orientation estimation. Therefore, this paper proposes a modified algorithm for 2D anisotropic Gaussian filters and shows that this improves their precision. Applied to synthetic images of fiber bundles, it is more accurate and robust to noise. Finally, the effectiveness of the approach is shown by applying it to real-world images of sheet molding compounds.

翻译：细长各向异性高斯滤波器用于纤维取向估计。在计算机断层扫描图像存在噪声、分辨率较低且对比度不足的情况下，即使该方法仅在虚拟二维切片中有效，它仍是首选方案。然而，各向异性高斯滤波器的微小误差会传导至取向估计结果。为此，本文提出一种改进的二维各向异性高斯滤波算法，并证明该算法能提升精度。在合成纤维束图像上的实验表明，该方法具有更高的准确性和更强的抗噪鲁棒性。最后，通过将其应用于片状模塑料的真实图像，验证了该方法的有效性。