Computer Vision, Graphics, and Image Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
A taxonomy for texture description and identification
A taxonomy for texture description and identification
Fast B-spline Transforms for Continuous Image Representation and Interpolation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
FVC2000: Fingerprint Verification Competition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Framework for Segmentation and Grouping
Computational Framework for Segmentation and Grouping
Multidimensional Digital Signal Processing
Multidimensional Digital Signal Processing
Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Steerable-Scalable Kernels for Edge Detection and Junction Analysis
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Estimating local multiple orientations
Signal Processing
High Frequency Assessment from Multiresolution Analysis
ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I
Multi-view and Multi-scale Recognition of Symmetric Patterns
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Offline handwritten Amharic word recognition
Pattern Recognition Letters
Detection of spots in 2-d electrophoresis gels by symmetry features
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Registration of fingerprints by complex filtering and by 1d projections of orientation images
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Local orientation estimation in corrupted images
IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
Local feature extraction in fingerprints by complex filtering
IWBRS'05 Proceedings of the 2005 international conference on Advances in Biometric Person Authentication
Particle filtering in the Hough space for instrument tracking
Computers in Biology and Medicine
Tensor scale: An analytic approach with efficient computation and applications
Computer Vision and Image Understanding
Recognition of Ethiopic braille characters
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
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We suggest a set of complex differential operators that can be used to produce and filter dense orientation (tensor) fields for feature extraction, matching, and pattern recognition. We present results on the invariance properties of these operators, that we call symmetry derivatives. These show that, in contrast to ordinary derivatives, all orders of symmetry derivatives of Gaussians yield a remarkable invariance: They are obtained by replacing the original differential polynomial with the same polynomial, but using ordinary coordinatesxandy corresponding to partial derivatives. Moreover, the symmetry derivatives of Gaussians are closed under the convolution operator and they are invariant to the Fourier transform. The equivalent of the structure tensor, representing and extracting orientations of curve patterns, had previously been shown to hold in harmonic coordinates in a nearly identical manner. As a result, positions, orientations, and certainties of intricate patterns, e.g., spirals, crosses, parabolic shapes, can be modeled by use of symmetry derivatives of Gaussians with greater analytical precision as well as computational efficiency. Since Gaussians and their derivatives are utilized extensively in image processing, the revealed properties have practical consequences for local orientation based feature extraction. The usefulness of these results is demonstrated by two applications: 1) tracking cross markers in long image sequences from vehicle crash tests and 2) alignment of noisy fingerprints.