3D defects detection method based on serial slice images of cone-beam computed tomography

According to the isotropy of serial slice images of Cone-Beam Computed Tomography (CBCT) and the small displacement and little shape change of defect solids between slice images, a method of 3D defects detection for CBCT serial slice images is proposed. Firstly, the defect solids are labeled by multi-object tracking and 3D connective region extraction. The Hash table of correlative defects is establishes to solve the fork trajectory of defect targets. Then the fake defects are deleted by the inherent particularities of noise targets, so the final real defect targets are obtained and classified which precision of extracted defects is 3 × 3 × 3 pixels. This method is adopted to processing the CBCT serial slice images of wax model of hollow turbine blade. The experiment result shows that the 3D defects in the serial images corrupted by noises are extracted exactly.