spatialGradient: First Order Derivatives of an Image with the Sobel Operator
In neuroconductor-releases/Rvision: Basic Computer Vision Library
Description
Usage
Arguments
Value
Author(s)
See Also
Examples
Description
spatialGradient calculates the first order derivative of
an image in both x and y using a Sobel operator.
Usage
1
spatialGradient(image, k_size = 5)
Arguments
image
An Image object.
k_size
The half-size in pixels of the kernel (default: 5).
Value
image An Image object.
Author(s)
Simon Garnier, garnier@njit.edu
See Also
Examples
1
# TODO
neuroconductor-releases/Rvision documentation built on Nov. 10, 2020, 9:10 p.m.
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Description Usage Arguments Value Author(s) See Also Examples
Description
spatialGradient calculates the first order derivative of
an image in both x and y using a Sobel operator.
Usage
1 | spatialGradient(image, k_size = 5)
|
Arguments
image |
An |
k_size |
The half-size in pixels of the kernel (default: 5). |
Value
image An Image object.
Author(s)
Simon Garnier, garnier@njit.edu
See Also
Examples
1 | # TODO
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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