Inline videos. See also:Category: Articles with embedded Videos..

Sobel

From Biocrawler, the free encyclopedia.

In image processing, 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 \mathbf{A} as the source image, we can compute:

\mathbf{G_x} = \begin{bmatrix}  -1 & 0 & +1 \\ -2 & 0 & +2 \\ -1 & 0 & +1  \end{bmatrix} * \mathbf{A} \ and\  \mathbf{G_y} = \begin{bmatrix}  +1 & +2 & +1 \\ 0 & 0 & 0 \\ -1 & -2 & -1  \end{bmatrix} * \mathbf{A}

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

\mathbf{G} = \sqrt{ \mathbf{G_x}^2 + \mathbf{G_y}^2 }

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

\mathbf{\Theta} = \operatorname{arctan}\left({ \mathbf{G_y} \over \mathbf{G_x} }\right)

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

See also

Wikipedia (http://en.wikipedia.org/wiki/Main_Page) Sobel (http://en.wikipedia.org/wiki/Sobel) version history (http://en.wikipedia.org/w/index.php?title=Sobel&action=history) GNU Free Documentation Lizenz (http://en.wikipedia.org/wiki/Wikipedia:Text_of_the_GNU_Free_Documentation_License) CC-by-sa (http://creativecommons.org/licenses/by-sa/2.5/)

Personal tools
Google Search
Google
Web
biocrawler.com

 
In other languages