An Optimized Segmentation Algorithm for the Surface Extraction in Computed Tomography for Metrology Applications

Abstract The CT process for metrology applications is very complex because has many factors that influence the loss of accuracy during CT measurements. One of the most critical is the edge detection also called surface extraction or image segmentation, which is the process of surface formation from the CT‘s volume data that represents a grey value corresponding to the mass attenuation coefficient of the object material. This paper presents three edge detection methods commonly used in areas like machine and computer vision and they are analyzed as an alternative to the common methods used in CT for metrology applications. An experimental comparative between the three techniques is also shown, using them on three different parts: two reference parts and one industrial part.