A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Algorithms for Low-Level Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale and the differential structure of images
Image and Vision Computing - Special issue: information processing in medical imaging 1991
Steerable-scalable kernels for edge detection and junction analysis
Image and Vision Computing - Special issue: 2nd European Conference on Computer Vision
Distributed representation and analysis of visual motion
Distributed representation and analysis of visual motion
Recursive implementation of the Gaussian filter
Signal Processing
Direct computation of shape cues using scale-adapted spatial derivative operators
International Journal of Computer Vision - Special issue: machine vision research at the Royal Institute of Technology
An Unbiased Detector of Curvilinear Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Minimum Cost Approach for Segmenting Networks of Lines
International Journal of Computer Vision
Geometry-Driven Diffusion in Computer Vision
Geometry-Driven Diffusion in Computer Vision
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Invertible Orientation Bundles on 2D Scalar Images
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Edge Detection and Ridge Detection with Automatic Scale Selection
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Recursive Gaussian Derivative Filters
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Fingerprint enhancement by shape adaptation of scale-space operators with automatic scale selection
IEEE Transactions on Image Processing
ISCGAV'08 Proceedings of the 8th conference on Signal processing, computational geometry and artificial vision
Ridges and valleys detection in images using difference of rotating half smoothing filters
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
A real-time gabor primal sketch for visual attention
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
Parametric visualization of high resolution correlated multi-spectral features using PCA
EUROVIS'07 Proceedings of the 9th Joint Eurographics / IEEE VGTC conference on Visualization
User transparent data and task parallel multimedia computing with Pyxis-DT
Future Generation Computer Systems
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We derive the decomposition of the anisotropic Gaussian in a one dimensional Gauss filter in the x-direction followed by a one dimensional filter in a non-orthogonal direction 驴. So also the anisotropic Gaussian can be decomposed by dimension. This appears to be extremely efficient from a computing perspective. An implementation scheme for normal convolution and for recursive filtering is proposed. Also directed derivative filters are demonstrated.For the recursive implementation, filtering an 512 脳 512 image is performed within 65 msec, independent of the standard deviations and orientation of the filter. Accuracy of the filters is still reasonable when compared to truncation error or recursive approximation error.The anisotropic Gaussian filtering method allows fast calculation of edge and ridge maps, with high spatial and angular accuracy. For tracking applications, the normal anisotropic convolution scheme is more advantageous, with applications in the detection of dashed lines in engineering drawings. The recursive implementation is more attractive in feature detection applications, for instance in affine invariant edge and ridge detection in computer vision. The proposed computational filtering method enables the practical applicability of orientation scale-space analysis.