IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-linearities in cortical simple cells and the possible detection of zero crossings
Biological Cybernetics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Singularity Theory and Phantom Edges in Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scaling Theorems for Zero-Crossings
Scaling Theorems for Zero-Crossings
Singularity Theory and Phantom Edges in Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extensions of Scale-Space Filtering to Machine-Sensing Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Directional Analysis of Images in Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple Widths Yield Reliable Finite Differences (Computer Vision)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Some Defects in Finite-Difference Edge Finders
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Transform for Multiscale Image Segmentation by Integrated Edge and Region Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Differentiation-Based Edge DetectionUsing the Logarithmic Image Processing Model
Journal of Mathematical Imaging and Vision
Scale-Space Derived From B-Splines
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Location Error of Curved Edges in Low-Pass Filtered 2-D and 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation of black and white cartoons
SCCG '03 Proceedings of the 19th spring conference on Computer graphics
Feature selection of 3D volume data through multi-dimensional transfer functions
Pattern Recognition Letters
Distributed recursive learning for shape recognition through multiscale trees
Image and Vision Computing
A new edge detector based on Fresnel diffraction
Pattern Recognition Letters
Multi-resolution system for artifact removal and edge enhancement in computerized tomography images
Pattern Recognition Letters
Detection of Edges in Spectral Data III--Refinement of the Concentration Method
Journal of Scientific Computing
Colorization of black-and-white cartoons
Image and Vision Computing
Edge detection based on asymptote model
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Local estimation of Gaussian-based edge enhancement filters using Fourier analysis
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
Motion estimation with wavelet transform and the application to motion compensated interpolation
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
Reducing aliasing in images: a PDE-based diffusion revisited
Pattern Recognition
Fast measuring particle size by using the information of particle boundary and shape
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Real-time architecture for a robust multi-scale stereo engine on FPGA
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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It is shown that zero-crossing edge detection algorithms can produce edges that do not correspond to significant image intensity changes. Such edges are called phantom or spurious. A method for classifying zero crossings as corresponding to authentic or phantom edges is presented. The contrast of an authentic edge is shown to increase and the contrast of phantom edges to decrease with a decrease in the filter scale. Thus, a phantom edge is truly a phantom in that the closer one examines it, the weaker it becomes. The results of applying the classification schemes described to synthetic and authentic signals in one and two dimensions are given. The significance of the phantom edges is examined with respect to their frequency and strength relative to the authentic edges, and it is seen that authentic edges are denser and stronger, on the average, than phantom edges.