5,321
edits
Geometric Computer Vision: Difference between revisions
→Image Gradients
No edit summary |
|||
| Line 13: | Line 13: | ||
===Image Gradients=== | ===Image Gradients=== | ||
* Angle is given by <math>\theta = \arctan(\frac{ | * Angle is given by <math>\theta = \arctan(\frac{\partial f}{\partial y}, \frac{\partial f}{\partial x})</math> | ||
* Edge strength is given by <math>\left\Vert (\frac{ | * Edge strength is given by <math>\left\Vert (\frac{\partial f}{\partial x}, \frac{\partial f}{\partial y}) \right\Vert</math> | ||
Sobel operator is another way to approximate derivatives:<br> | |||
<math> | |||
s_x = | |||
\frac{1}{8} | |||
\begin{bmatrix} | |||
-1 & 0 & 1\\ | |||
-2 & 0 & 2\\ | |||
-1 & 0 & 1 | |||
\end{bmatrix} | |||
</math>, | |||
<math> | |||
s_y = | |||
\frac{1}{8} | |||
\begin{bmatrix} | |||
1 & 2 & 1\\ | |||
0 & 0 & 0\\ | |||
-1 & -2 & -1 | |||
\end{bmatrix} | |||
</math> | |||