Comparing edge-detection algorithm performance under degrading signal-to-noise ratio conditions

Kelce S. Wilson

doi:10.1117/12.421139

20 March 2001 Comparing edge-detection algorithm performance under degrading signal-to-noise ratio conditions

Kelce S. Wilson

Proceedings Volume 4387, Optical Pattern Recognition XII; (2001) https://doi.org/10.1117/12.421139
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

A metric is developed for evaluating performance degradation of edge detection algorithms as a function of signal to noise ratio (SNR). The metric combines both missed detections and false alarms to form a composite score. This provides a basis for objectively comparing the performance of different techniques and quantifies relative noise tolerance. It is applied to various popular algorithms, Sobel, Roberts, Prewitt, and Laplacian of Gaussian, but is described in sufficient detail to facilitate easy application to other edge detection methods. Results shown allow selection of the most optimum method for application to images with known SNR levels.

Citation Download Citation

Kelce S. Wilson "Comparing edge-detection algorithm performance under degrading signal-to-noise ratio conditions", Proc. SPIE 4387, Optical Pattern Recognition XII, (20 March 2001); https://doi.org/10.1117/12.421139

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