A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge detection and motion detection
Image and Vision Computing
Localization and Noise in Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Optimal Infinite Impulse Response Edge Detection Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel Designs for Efficient Multiresolution Edge Detection and Orientation Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Edge Location Error for Local Maximum and Zero-Crossing Edge Detectors
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection with Embedded Confidence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Signal differentiation through a Green's function approach
Pattern Recognition Letters
A Regularized Solution to Edge Detection
A Regularized Solution to Edge Detection
Canny Edge Detection Enhancement by Scale Multiplication
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Step Edges from Zero Crossing of Second Directional Derivatives
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge detection in untextured and textured images-a common computational framework
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On optimal linear filtering for edge detection
IEEE Transactions on Image Processing
A Comparative analysis of Green's functions of 1D matching equations for motion synthesis
Pattern Recognition Letters
| Hi-index | 0.10 |
The estimation of derivatives is an important and sensitive task in digital image processing and analysis, both accuracy and computational efficiency being expected of a differential operator. Here we propose a new filter-designed through a strategy based on the Green's function of a signal matching equation-that responds to such demands. When used for edge detection, it yields theoretical performance indices that rival, and even top, the best reported marks. It is also computationally efficient, allowing very simple recursive implementation. The results of extensive edge-detection experimentation are reported here. Being explicitly designed as a first-derivative operator, our filter should also find application in other signal processing domains.