Howtosignalprocessing
- How derivatives are used for edge detection?
- What is Gaussian derivative filter?
- What is the derivative of a Gaussian?
- What is the disadvantage of using a second order derivative filters for edge detection?
How derivatives are used for edge detection?
In this method we take the 1st derivative of the intensity value across the image and find points where the derivative is maximum then the edge could be located. The gradient is a vector, whose components measure how rapid pixel value are changing with distance in the x and y direction.
What is Gaussian derivative filter?
In electronics and signal processing mainly in digital signal processing, a Gaussian filter is a filter whose impulse response is a Gaussian function (or an approximation to it, since a true Gaussian response would have infinite impulse response).
What is the derivative of a Gaussian?
Mathematically, the derivatives of the Gaussian function can be represented using Hermite functions. For unit variance, the n-th derivative of the Gaussian is the Gaussian function itself multiplied by the n-th Hermite polynomial, up to scale.
What is the disadvantage of using a second order derivative filters for edge detection?
However there are disadvantages to the use of second order derivatives. (We should note that first derivative operators exaggerate the effects of noise.) Second derivatives will exaggerated noise twice as much. No directional information about the edge is given.
