A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scaling Theorems for Zero Crossings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Uniqueness of the Gaussian Kernel for Scale-Space Filtering
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
Pulse and staircase edge models
Computer Vision, Graphics, and Image Processing
Authenticating Edges Produced by Zero-Crossing Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Authenticating Edges Produced by Zero-Crossing Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple Widths Yield Reliable Finite Differences (Computer Vision)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Based Detection of Corners of Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reasoning About Edges in Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space Properties of Quadratic Feature Detectors
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multiscale Model for Structure-Based Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Pattern Analysis and Machine Intelligence
The shape of handwritten characters
Pattern Recognition Letters
A fast multi-scale edge detection algorithm
Pattern Recognition Letters
Edge structure preserving image denoising
Signal Processing
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
Teaching a humanoid robot to draw `Shapes'
Autonomous Robots
| Hi-index | 0.14 |
The process of detecting edges in a one-dimensional signal by finding the zeros of the second derivative of the signal can be interpreted as the process of detecting the critical points of a general class of contrast functions that are applied to the signal. It is shown that the second derivative of the contrast function at the critical point is related to the classification of the associated edge as being phantom or authentic. The contrast of authentic edges decreases with filter scale, while the contrast of phantom edges are shown to increase with scale. As the filter scale increases, an authentic edge must either turn into a phantom edge or join with a phantom edge and vanish. The points in the scale space at which these events occur are seen to be singular points of the contrast function. Using ideas from singularity, or catastrophy theory, the scale map contours near these singular points are found to be either vertical or parabolic.