πCommon Concepts
Last updated
Last updated
We did element wise product then we get the sum of the result matrix; so:
And so on for other elements π
An application of convolution operation
Result: horizontal lines pop out
Result: vertical lines pop out
There are a lot of ways we can put number inside elements of the filter.
For example Sobel filter is like:
Scharr filter is like:
Prewitt filter is like:
So the point here is to pay attention to the middle row
And Roberts filter is like:
We can tune these numbers by ML approach; we can say that the filter is a group of weights that:
By that we can get -learned- horizontal, vertical, angled, or any edge type automatically rather than getting them by hand.
If we have an n*n
image and we convolve it by f*f
filter the the output image will be n-f+1*n-f+1
π If we apply many filters then our image shrinks.
π€¨ Pixels at corners aren't being touched enough, so we are throwing away a lot of information from the edges of the image .
We can pad the image πͺ
Term
Description
Convolution
Applying some filter on an image so certain features in the image get emphasized