Digital topology: introduction and survey
Computer Vision, Graphics, and Image Processing
On connectivity issues of ESPTA
Pattern Recognition Letters
Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
A parallel thinning algorithm for medial surfaces
Pattern Recognition Letters
Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
A fully parallel 3D thinning algorithm and its applications
Computer Vision and Image Understanding
Image Processing with Complex Daubechies Wavelets
Journal of Mathematical Imaging and Vision
A 3D 6-subiteration thinning algorithm for extracting medial lines
Pattern Recognition Letters
An Analysis of the Fundamental Structure of Complex-Valued Neurons
Neural Processing Letters
A 3-subiteration 3D thinning algorithm for extracting medial surfaces
Pattern Recognition Letters
A medial-surface oriented 3-d two-subfield thinning algorithm
Pattern Recognition Letters
Discrete Wavelet Analysis: A New Framework for Fast Optic Flow Computation
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Directional, shift-insensitive, complex wavelet transforms with controllable redundancy
Directional, shift-insensitive, complex wavelet transforms with controllable redundancy
Complex-Valued Neural Networks: Theories and Applications (Series on Innovative Intelligence, 5)
Complex-Valued Neural Networks: Theories and Applications (Series on Innovative Intelligence, 5)
Computers in Biology and Medicine
Hypercomplex signals-a novel extension of the analytic signal tothe multidimensional case
IEEE Transactions on Signal Processing
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
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Curve and surface thinning are widely-used skeletonization techniques for modeling objects in three dimensions. In the case of disordered porous media analysis, however, neither is really efficient since the internal geometry of the object is usually composed of both rod and plate shapes. This paper presents an alternative to compute a hybrid shape-dependant skeleton and its application to porous media. The resulting skeleton combines 2D surfaces and 1D curves to represent respectively the plate-shaped and rod-shaped parts of the object. For this purpose, a new technique based on neural networks is proposed: cascade combinations of complex wavelet transform (CWT) and complex-valued artificial neural network (CVANN). The ability of the skeleton to characterize hybrid shaped porous media is demonstrated on a trabecular bone sample. Results show that the proposed method achieves high accuracy rates about 99.78%---99.97%. Especially, CWT (2nd level)-CVANN structure converges to optimum results as high accuracy rate--minimum time consumption.