A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge detection and motion detection
Image and Vision Computing
Digital image processing
Optimal Edge Detectors for Ramp Edges
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
Optimal Edge Detection using Expansion Matching and Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Activity Recognition Using Multidimensional Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning, detection and representation of multi-agent events in videos
Artificial Intelligence
Optimal edge detection using perfect sharpening of ramp edges
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
Edge Detection Filter based on Mumford-Shah Green Function
SIAM Journal on Imaging Sciences
Two-dimensional multi-pixel anisotropic Gaussian filter for edge-line segment (ELS) detection
Image and Vision Computing
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In practical images, ideal step edges are actually transformed into ramp edges, due to the general low pass filtering nature of imaging systems. This paper discusses the application of the recently developed Expansion Matching (EXM) method for optimal ramp edge detection. EXM optimizes a novel matching criterion called Discriminative Signal-to-Noise Ratio (DSNR) and has been shown to robustly recognize templates under conditions of noise, severe occlusion, and superposition. We show that our ramp edge detector performs better than the ramp detector obtained from Canny's criteria in terms of DSNR and is relatively easier to derive for various noise levels and slopes.