The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Signal Processing for Computer Vision
Signal Processing for Computer Vision
Coherence-Enhancing Diffusion Filtering
International Journal of Computer Vision
Integrated Edge and Junction Detection with the Boundary Tensor
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
GET: the connection between monogenic scale-space and gaussian derivatives
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
IEEE Transactions on Signal Processing
Signal modeling for two-dimensional image structures
Journal of Visual Communication and Image Representation
Analyzing Image Structure by Multidimensional Frequency Modulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analysis of multiple orientations
IEEE Transactions on Image Processing
Journal of Mathematical Imaging and Vision
Multiscale AM-FM demodulation and image reconstruction methods with improved accuracy
IEEE Transactions on Image Processing
Local structure analysis by isotropic hilbert transforms
Proceedings of the 32nd DAGM conference on Pattern recognition
Representing local structure using tensors II
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
GET: the connection between monogenic scale-space and gaussian derivatives
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
A theory of multiple orientation estimation
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
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Traditionally, quadrature filters and derivatives have been considered as alternative approaches to low-level image analysis. In this paper we show that there actually exist close connections: We define the quadrature-based boundary tensor and the derivative-based gradient energy tensor which exhibit very similar behavior. We analyse the reason for this and determine how to minimize the difference. These insights lead to a simple and very efficient integrated feature detection algorithm.