Package boofcv.alg.filter.derivative

Class GradientSobel

java.lang.Object

boofcv.alg.filter.derivative.GradientSobel

public class GradientSobel
extends Object

Computes the image's first derivative along the x and y axises using the Sobel operator.

The Sobel kernel weights the inner most pixels more than ones farther away. This tends to produce better results, but not as good as a gaussian kernel with larger kernel. However, it can be optimized so that it is much faster than a Gaussian.

For integer images, the derivatives in the x and y direction are computed by convolving the following kernels:

y-axis

</table} x-axis

-0.25	-0.5	-0.25
0	0	0
0.25	0.5	0.25

</table} Floating point images use a kernel which is similar to the ones above, but divided by 4.0. As a side note, the sobel operator is equivalent to convolving the image with the following 1D kernels: conv2( [0.25 0.5 0.25], [-1 0 1] )

Field Summary

Fields

Modifier and Type	Field	Description
static Kernel2D_F32	kernelDerivX_F32
static Kernel2D_S32	kernelDerivX_I32
static Kernel2D_F32	kernelDerivY_F32
static Kernel2D_S32	kernelDerivY_I32

Constructor Summary

Constructors

Constructor	Description
GradientSobel()

Method Summary

Modifier and Type	Method	Description
static Kernel2D	getKernelX(boolean isInteger)	Returns the kernel for computing the derivative along the x-axis.
static void	process(GrayF32 orig, GrayF32 derivX, GrayF32 derivY, @Nullable ImageBorder_F32 border)	Computes the derivative in the X and Y direction using an integer Sobel edge detector.
static void	process(GrayS16 orig, GrayS16 derivX, GrayS16 derivY, @Nullable ImageBorder_S32<GrayS16> border)	Computes the derivative in the X and Y direction using an integer Sobel edge detector.
static void	process(GrayU8 orig, GrayS16 derivX, GrayS16 derivY, @Nullable ImageBorder_S32<GrayU8> border)	Computes the derivative in the X and Y direction using an integer Sobel edge detector.
static <I extends ImageGray<I>, D extends ImageGray<D>> void	process(I input, D derivX, D derivY, @Nullable ImageBorder border)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

kernelDerivX_I32

public static Kernel2D_S32 kernelDerivX_I32

kernelDerivY_I32

public static Kernel2D_S32 kernelDerivY_I32

kernelDerivX_F32

public static Kernel2D_F32 kernelDerivX_F32

kernelDerivY_F32

public static Kernel2D_F32 kernelDerivY_F32

Constructor Details

GradientSobel

public GradientSobel()

Method Details

getKernelX

public static Kernel2D getKernelX(boolean isInteger)

Returns the kernel for computing the derivative along the x-axis.

process

public static <I extends ImageGray<I>,
D extends ImageGray<D>>
void process(I input,
 D derivX,
 D derivY,
 @Nullable
 @Nullable ImageBorder border)

process

public static void process(GrayU8 orig,
 GrayS16 derivX,
 GrayS16 derivY,
 @Nullable
 @Nullable ImageBorder_S32<GrayU8> border)

Computes the derivative in the X and Y direction using an integer Sobel edge detector.

Parameters:

orig - Input image. Not modified.

derivX - Storage for image derivative along the x-axis. Modified.

derivY - Storage for image derivative along the y-axis. Modified.

border - Specifies how the image border is handled. If null the border is not processed.

process

public static void process(GrayS16 orig,
 GrayS16 derivX,
 GrayS16 derivY,
 @Nullable
 @Nullable ImageBorder_S32<GrayS16> border)

Computes the derivative in the X and Y direction using an integer Sobel edge detector.

Parameters:

orig - Input image. Not modified.

derivX - Storage for image derivative along the x-axis. Modified.

derivY - Storage for image derivative along the y-axis. Modified.

border - Specifies how the image border is handled. If null the border is not processed.

process

public static void process(GrayF32 orig,
 GrayF32 derivX,
 GrayF32 derivY,
 @Nullable
 @Nullable ImageBorder_F32 border)

Computes the derivative in the X and Y direction using an integer Sobel edge detector.

Parameters:

orig - Input image. Not modified.

derivX - Storage for image derivative along the x-axis. Modified.

derivY - Storage for image derivative along the y-axis. Modified.

border - Specifies how the image border is handled. If null the border is not processed.

-1	0	1
-2	0	2
-1	0	1