Sobel, Scharr and Laplacian: How Three Edge Detectors Differ in OpenCV

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This DEV Community article explains edge detection in digital image processing, which locates regions where pixel intensity changes sharply, such as object boundaries. It describes three widely used operators: Sobel and Scharr, which are first-order derivative methods that estimate gradients in two directions, and the Laplacian, which relies on second-order derivatives. The author outlines the mathematical basis of each, noting Scharr's improved rotational symmetry and the Laplacian's high sensitivity to noise. The piece then implements all three in Python with OpenCV, applying them to the same image and comparing their outputs, with Gaussian smoothing used beforehand to reduce noise.

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Claude Code Action Can Automatically Review GitHub Pull Requests

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ProgrammingDEV Community ·

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