To filter an image it is filtered using both operators the results of which are added together. In this post, we learn about the Sobel Filter in Image Processing which is also called the Edge Detector Filter in Image Processing.
The Sobel edge detector is a gradient-based method. Sobel filters are typically used for edge detection.
Also Read: High Pass Filter in Image Processing
Sobel Filter / Edge Detector in Image Processing
- It works with first-order derivatives.
- It calculates the first derivatives of the image separately for the X and Y axes.
- The derivatives are only approximations (because the images are not continuous).
- To approximate them, the following kernels are used for convolution:
The kernel on the left approximates the derivative along the X-axis.
The one on the right is for the Y-axis. Using this information, you can calculate the following:
- Magnitude or “strength” of the edge:
- Approximate strength:
- The orientation of the edge:
Above, I’ve detected horizontal peaks. You can clearly see the horizontal edges highlighted.
You can then threshold this result to get rid of the grey areas and get solid edges.