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Edge Detection

Detect and visualize edges in any image. Choose between Canny, Sobel, Laplace, Scharr, and Prewitt algorithms to highlight contours, boundaries, and structural details.

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Edge Detection

Run Canny, Sobel, Laplacian, Scharr, and Prewitt edge detection online to visualize boundaries, gradients, and structural detail.

Detect and visualize edges in any image. Choose between Canny, Sobel, Laplace, Scharr, and Prewitt algorithms to highlight contours, boundaries, and structural details.

How to Use Edge Detection

  1. Upload an image: Upload one of the formats listed by the tool (JPG, PNG, WebP) and wait for the local preview.
  2. Adjust settings and process: Choose the edge detection algorithm (Canny, Sobel, Laplace, Scharr, or Prewitt) and adjust the threshold and aperture parameters.
  3. Review and download: Review the result, then download it in one of the formats offered by this tool.

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.

Is the Edge Detection tool free?

Yes. All tools on Pixlane are free with no signup required. It runs in your browser with no server upload.

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