AbstractScientific digital imaging in three dimensions such as when using X-ray computed tomography offers a variety of ways to obtain, filter, and quantify data that can produce vastly different results. These opportunities, performed during image acquisition or during the data processing, can include filtering, cropping, and setting thresholds. Quantifying features in these images can be greatly affected by how the above operations are performed. For example, during binarization, setting the threshold too low or too high can change the number of objects as well as their measured diameter. Here, two facets of three-dimensional quantification are explored. The first will focus on investigating the question of how many voxels are needed within an object to have accurate geometric statistics that are due to the properties of the object and not an artifact of too few voxels. These statistics include but are not limited to percent of total volume, volume of the individual object, Feret shape, and surface area. Using simple cylinders as a starting point, various techniques for smoothing, filtering, and other processing steps can be investigated to aid in determining if they are appropriate for a specific desired statistic for a real dataset. The second area of investigation is the influence of post-processing, particularly segmentation, on measuring the damage statistics in high purity Cu. The most important parts of the pathways of processing are highlighted.
Research on latent defect detection technology of high voltage cable