Comparing edge detection algorithm performance under degrading signal to noise ratio conditions
نویسنده
چکیده
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.
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