A Computational Approach to Edge Detection
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 Edge Detectors for Ramp Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
The local structure of space-variant images
Neural Networks
A Discrete Expression of Canny's Criteria for Step Edge Detector Performances Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A review of biologically motivated space-variant data reduction models for robotic vision
Computer Vision and Image Understanding
Primal sketch feature extraction from a log-polar image
Pattern Recognition Letters - Special issue: Sibgrapi 2001
A review of log-polar imaging for visual perception in robotics
Robotics and Autonomous Systems
Pattern Recognition Letters
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In a continuous sense, images and gradient operators can be mapped conformally between Cartesian and log-polar (LP) space and the process of gradient detection can be shown to be equivalent. However, gains in the efficiency of processing LP and other retino-cortical image mappings rely on variable sampling with a high resolution fovea and much lower resolution towards the periphery. In this paper, we consider the implementation and evaluation of three strategies for gradient detection in a space-variant, sampled LP geometry.