Shape reconstruction and inspection using multi-planar X-ray images

Computer-aided manufacturing is widely used to create products from computer-aided design (CAD) models. The different characteristics of each manufacturing process can lead to product defects. Therefore, it is necessary to inspect the shape and dimensions of a manufactured product against the original CAD model for quality assurance. While the conventional laser-based three-dimensional (3D) scanning allows reconstruction of the external shape of an object, X-ray imaging can capture the internal shape. Aided by digital radiographic techniques, X-ray images can be captured within a few milliseconds. In this study, we used multiple X-ray images of an object to reconstruct its geometry and topology. Each of the two-dimensional (2D) X-ray images was processed to detect object edges. Using the geometric calibration information of the X-ray imaging system, the 3D vertices of the object were reconstructed. The topology, edges connecting vertices, was reconstructed by re-projecting the vertices to the X-ray images. The reconstructed object shape was statistically analyzed to understand the effects of the number of views and the parameters used in the reconstruction process on the accuracy of the reconstructed geometries. For our target objects, images from more than seven different views were used to successfully reconstruct the full shape of the object.

[1]  Albert Macovski,et al.  Medical imaging systems , 1983 .

[2]  Roberto Cesareo,et al.  Computed tomography with image intensifier: potential use for nondestructive testing and imaging of small objects , 2000 .

[3]  Seokbae Son,et al.  Automated laser scanning system for reverse engineering and inspection , 2002 .

[4]  Russell H. Taylor,et al.  Fast algorithm for probabilistic bone edge detection (FAPBED) , 2005, SPIE Medical Imaging.

[5]  Joon Hyun Kim,et al.  Development of 3-D shapes estimation by using single X-ray image , 2009, 2009 International Symposium on Optomechatronic Technologies.

[6]  Fangzhou Zhang,et al.  X-Ray Image Edge Detection Based on Wavelet Transform and Lipschitz Exponent , 2009, 2009 Second International Symposium on Intelligent Information Technology and Security Informatics.

[7]  Min Kook Cho,et al.  Cone-beam digital tomosynthesis for thin slab objects , 2012 .

[8]  W. Gander,et al.  Least-squares fitting of circles and ellipses , 1994 .

[9]  Laurent Desbat,et al.  Edge detection and classification in X-ray images. Application to interventional 3D vertebra shape reconstruction. , 2005 .

[10]  Rufus H. Cofer,et al.  Extended Hough transform for linear feature detection , 2006, Pattern Recognit..

[11]  N. Chernov.  Circular and Linear Regression: Fitting Circles and Lines by Least Squares , 2010 .

[12]  Guoyan Zheng.  3D volumetric intensity reconsturction from 2D x-ray images using partial least squares regression , 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

[13]  Joo Hyun Kim,et al.  Detection of Flip-chip Bonding Error Through Edge Size Extraction of X-ray Image , 2009 .

[14]  D. Donoho,et al.  Does median filtering truly preserve edges better than linear filtering , 2006, math/0612422.

[15]  Cécile Barat,et al.  Segmentation of blurred objects using wavelet transform: application to x-ray images , 2004, SPIE Optics East.

[16]  Thomas R Oxland,et al.  Improved RSA accuracy with DLT and balanced calibration marker distributions with an assessment of initial-calibration. , 2003, Journal of biomechanics.

[17]  Mirigul Altan,et al.  Reducing shrinkage in injection moldings via the Taguchi, ANOVA and neural network methods , 2010 .

[18]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[19]  Jae Wan Kim,et al.  6-DOF pose estimation of polyhedral objects based on analysis of geometric features in x-ray images , 2001, Optics East.

[20]  T Aach,et al.  Digital radiography enhancement by nonlinear multiscale processing. , 2000, Medical physics.

[21]  Kwang-Baek Kim,et al.  Optimal Parameter Selection in Edge Strength Hough Transform , 2007 .

[22]  Min Kook Cho,et al.  Performance characterization of microtomography with complementary metal-oxide-semiconductor detectors for computer-aided defect inspection , 2009 .

[23]  S. Kamata,et al.  High energy X-ray computed tomography for industrial applications , 1991, Conference Record of the 1991 IEEE Nuclear Science Symposium and Medical Imaging Conference.

[24]  Elliot R. McVeigh,et al.  2D/3D registration for X-ray guided bronchoscopy using distance map classification , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.