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A method for edge detection that involves smoothing the image with a Gaussian filter before applying the Laplacian.

The Canny edge detector is a multi-stage algorithm designed to detect a wide range of edges in images.

The Laplacian operator measures the second derivative of the image to detect regions where rapid intensity change occurs.

Uses a pair of 2x2 convolution kernels to compute a simple, quick to compute approximation of the gradient.

Stands for Laplacian of Gaussian, and it is used to detect edges by zeroing on the rate of intensity change in an image after it has been smoothed with a Gaussian filter.

The Sobel operator uses convolution with Sobel kernels to calculate the gradient magnitude of the image for edge detection.

An edge detection operator that offers better rotation symmetry than Sobel and Prewitt operators.

An edge detection operator that identifies edges where the sign of the gradient of the image intensity changes, which correspond to zero crossings of the second derivative.

Utilizes eight possible convolution masks to compute edge magnitude, allowing for edge detection in multiple directions.