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- Ian T. Young, Lucas J. van Vliet, Michael van Ginkel
- IEEE Trans. Signal Processing
- 2000

—In this paper, we present a stable, recursive algorithm for the Gabor filter that achieves—to within a multiplicative constant—the fastest possible implementation. For a signal consisting of samples, our implementation requires () multiply-and-add (MADD) operations, that is, the number of computations per input sample is constant. Further, the complexity… (More)

Filtering of an image with rotated versions of an orientation selective filter yields a set of images which can be stacked to form an orientation space. Orientation space provides a means of analyzing overlapping and touching patterns, characterized by their orientation. In this paper we extend previous work and show that curved patterns may also be… (More)

We measure the sharpness of natural (complex) images using Gaussian models. We first locate lines and edges in the image. We apply Gaussian derivatives at different scales to the lines and edges. This yields a response function, to which we can fit the response function of model lines and edges. We can thus estimate the width and amplitude of the line or… (More)

- Joost van de Weijer, Lucas J. van Vliet, Piet W. Verbeek, Michael van Ginkel
- IEEE Trans. Pattern Anal. Mach. Intell.
- 2001

ÐCurved oriented patterns are dominated by high frequencies and exhibit zero gradients on ridges and valleys. Existing curvature estimators fail here. The characterization of curved oriented patterns based on translation invariance lacks an estimation of local curvature and yields a biased curvature-dependent confidence measure. Using parameterized… (More)

Extraction of primitives, such as lines, edges and curves, is often a key step in an image analysis procedure. The most popular technique for curve detection is based on the Hough transform. The original formulation of the Hough transform is inherently discrete. It is therefore difficult to assess which properties are inherent to the transform-based… (More)

- Cris L. Luengo Hendriks, Michael van Ginkel, Piet W. Verbeek, Lucas J. van Vliet
- Pattern Recognition
- 2005

The generalized Radon (or Hough) transform is a well-known tool for detecting parameterized shapes in an image. The Radon transform is a mapping between the image space and a parameter space. The coordinates of a point in the latter correspond to the parameters of a shape in the image. The amplitude at that point corresponds to the amount of evidence for… (More)

- M. van Ginkel
- 2001

We present a novel approach to parameterised curve detection. The method is based on the generalised Radon transform, which is traditionally applied to a 2D edge/line map. The novelty of our method is the mapping of the original 2D image to a 3D orientation space, which then forms the input for the Radon transform. The orientation space representation… (More)

In this technical report we compute the underestimation of the radius in the Radon transform for circles and spheres. Our implementation of the Radon transform uses spheres with a Gaussian profile, and normalises the grey-value of each of the spheres so that a very large sphere matching only a couple of segments will not get a higher confidence (value of… (More)

Filtering of an image with rotated versions of an orientation selective filter yields a set of images which can be stacked to form an orientation space. Orientation space provides a means of analyzing overlapping and touching anisotropic textures. A set of rotated k th order directional derivatives yields a discrete orientation space, which allows… (More)