A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
Subpixel Measurements Using a Moment-Based Edge Operator
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Localization Performance Measure and Optimal Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal infinite impulse response zero crossing based edge detectors
CVGIP: Image Understanding
On Optimal Infinite Impulse Response Edge Detection Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Field Categorization and Edge/Corner Detection from Gradient Covariance
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Canny Edge Detection Enhancement by Scale Multiplication
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient, recursively implemented differential operator, with application to edge detection
Pattern Recognition Letters
A new edge detector based on Fresnel diffraction
Pattern Recognition Letters
Image and Vision Computing
The Canny Edge Detector Revisited
International Journal of Computer Vision
Image feature detection from phase congruency based on two-dimensional Hilbert transform
Pattern Recognition Letters
| Hi-index | 0.15 |
Examines the localization criterion for edge detection and determine the probability density function describing the edge location error. Canny (1986) defines the measure of localization as the reciprocal of the root-mean-square edge location error and formulates an expression of this measure for local maximum detectors. However, Tagare and deFigueiredo (1990) point out that an incorrect assumption is made in the calculation. The same procedure is used by Sarkar and Boyer (1991) for their localization measure for zero-crossing detectors. We modify the analysis and obtain a closed-form solution of the probability density function of the edge location error. Examination of the density function indicates the variance of the edge location error does not exist, and hence cannot be used directly as a measure of localization.