Computer graphics: principles and practice (2nd ed.)
Computer graphics: principles and practice (2nd ed.)
A signal processing approach to fair surface design
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Interactive multi-resolution modeling on arbitrary meshes
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Implicit fairing of irregular meshes using diffusion and curvature flow
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Multiresolution signal processing for meshes
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Fast color texture recognition using chromaticity moments
Pattern Recognition Letters
Anisotropic geometric diffusion in surface processing
Proceedings of the conference on Visualization '00
Spectral processing of point-sampled geometry
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Anisotropic diffusion of surfaces and functions on surfaces
ACM Transactions on Graphics (TOG)
A simple algorithm for surface denoising
Proceedings of the conference on Visualization '01
Local Reproducible Smoothing Without Shrinkage
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generating Fair Meshes with G1 Boundary Conditions
GMP '00 Proceedings of the Geometric Modeling and Processing 2000
Mesh Smoothing via Mean and Median Filtering Applied to Face Normals
GMP '02 Proceedings of the Geometric Modeling and Processing — Theory and Applications (GMP'02)
Non-iterative, feature-preserving mesh smoothing
ACM SIGGRAPH 2003 Papers
ACM SIGGRAPH 2003 Papers
The trilateral filter for high contrast images and meshes
EGRW '03 Proceedings of the 14th Eurographics workshop on Rendering
SMI '02 Proceedings of the Shape Modeling International 2002 (SMI'02)
Fuzzy Vector Median-Based Surface Smoothing
IEEE Transactions on Visualization and Computer Graphics
Higher-Order Nonlinear Priors for Surface Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Feature Detection and Local Classification for Surfaces Based on Moment Analysis
IEEE Transactions on Visualization and Computer Graphics
ACM SIGGRAPH 2004 Papers
Interpolating and approximating implicit surfaces from polygon soup
ACM SIGGRAPH 2004 Papers
Spherical Diffusion for 3D Surface Smoothing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surface Reconstruction of Noisy and Defective Data Sets
VIS '04 Proceedings of the conference on Visualization '04
Spectral surface reconstruction from noisy point clouds
Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Robust moving least-squares fitting with sharp features
ACM SIGGRAPH 2005 Papers
An adaptive MLS surface for reconstruction with guarantees
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
Micro-crack inspection in heterogeneously textured solar wafers using anisotropic diffusion
Image and Vision Computing
Voreen: A Rapid-Prototyping Environment for Ray-Casting-Based Volume Visualizations
IEEE Computer Graphics and Applications
Wavelet based methods on patterned fabric defect detection
Pattern Recognition
| Hi-index | 0.00 |
The three-dimensional defect distribution in material test specimens is a very important piece of information for us to understand the deformation and failure mechanism of materials. This distribution is sometimes complicated by the surface roughness of specimens in the defect detection of computed tomography data. In this paper, we proposed a new local differentiation algorithm to remove the surface artifacts caused by surface roughness in the defect detection of material specimens from computed tomography (CT) volume data. The accuracy of our method is compared with a traditional scan-line algorithm in terms of defect volume fraction measured in an independent scanning electron microscope (SEM) test. The experimental result indicates that our method is significantly better than the existing scan-line approach for predicting the defect volume fraction.