In computer vision, the Sobel operator is a simple edge detection algorithm using the 1st derivative of the intensity information.

The operator uses two 3x3 kernels convolved with the original image to produce a map of intensity gradient. The areas of highest gradient are where the intensity of the image changes rapidly over a few pixels, and are thus likely to represent edges.

Two convolution kernels are needed to detect the first-order derivative of both horizontal and vertical changes in a 2-dimensional image. If we define as the source image, we can compute:

Which can then be combined to give the overall magnitudes using:

Using this information, we can also calculate the gradient's direction:

Where Θ will be 0 for a vertical edge, and will increase for edges anti-clockwise of this.

See also

• computer vision
• digital image processing
• edge detection
• feature extraction