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Edge Detection — Free Online Tool | Pixlane
Detect and visualize edges in any image. Choose between Canny, Sobel, Laplace, Scharr, and Prewitt algorithms to highlight contours, boundaries, and structural details.
Detect edges in images using Canny, Sobel, Laplace, Scharr, and Prewitt operators — visualize boundaries instantly.
All processing runs locally in your browser. Your files never leave your device — no upload, no server, no signup required.
Frequently Asked Questions
What is edge detection?
Edge detection identifies boundaries in images where brightness changes sharply. It is a fundamental operation in computer vision used for object recognition, image segmentation, and feature extraction.
What is the difference between Canny, Sobel, Laplace, Scharr, and Prewitt?
Canny is a multi-stage algorithm producing clean, thin edges with hysteresis. Sobel uses 3×3+ directional kernels. Scharr is an optimized 3×3 Sobel with better rotational symmetry. Laplace uses the second derivative, detecting edges in all directions. Prewitt uses simpler [-1,0,1] kernels for basic gradient estimation.
What do the threshold values mean?
In Canny edge detection, the low threshold filters out weak edges and the high threshold identifies strong edges. Pixels between the two thresholds are kept only if connected to strong edges (hysteresis).
What are dx and dy?
dx and dy control the derivative order in the X and Y directions. Setting dx=1,dy=0 detects vertical edges; dx=0,dy=1 detects horizontal edges. At least one must be non-zero.
What is kernel size?
The kernel size determines the convolution window used for gradient computation. Larger kernels (5×5, 7×7) smooth out noise but may miss fine details. 3×3 is the default for most applications.