boofcv.alg.filter.binary

Class GThresholdImageOps

java.lang.Object

boofcv.alg.filter.binary.GThresholdImageOps

public class GThresholdImageOps
extends Object

Weakly typed version of ThresholdImageOps.

Author:

Peter Abeles

Constructor Summary

Constructors

Constructor and Description
GThresholdImageOps()

Method Summary

Methods

Modifier and Type	Method and Description
static <T extends ImageSingleBand> ImageUInt8	adaptiveGaussian(T input, ImageUInt8 output, int radius, double bias, boolean down, T work1, T work2) Thresholds the image using an adaptive threshold that is computed using a local square region centered on each pixel.
static <T extends ImageSingleBand> ImageUInt8	adaptiveSquare(T input, ImageUInt8 output, int radius, double bias, boolean down, T work1, T work2) Thresholds the image using an adaptive threshold that is computed using a local square region centered on each pixel.
static <T extends ImageSingleBand> ImageUInt8	threshold(T input, ImageUInt8 output, double threshold, boolean down) Applies a global threshold across the whole image.

Methods inherited from class java.lang.Object

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

Constructor Detail

GThresholdImageOps

public GThresholdImageOps()

Method Detail

threshold

public static <T extends ImageSingleBand> ImageUInt8 threshold(T input,
                                               ImageUInt8 output,
                                               double threshold,
                                               boolean down)

Applies a global threshold across the whole image. If 'down' is true, then pixels with values <= to 'threshold' are set to 1 and the others set to 0. If 'down' is false, then pixels with values >= to 'threshold' are set to 1 and the others set to 0.

Parameters:

input - Input image. Not modified.

output - Binary output image. If null a new image will be declared. Modified.

threshold - threshold value.

down - If true then the inequality <= is used, otherwise if false then >= is used.

Returns:

Output image.

adaptiveSquare

public static <T extends ImageSingleBand> ImageUInt8 adaptiveSquare(T input,
                                                    ImageUInt8 output,
                                                    int radius,
                                                    double bias,
                                                    boolean down,
                                                    T work1,
                                                    T work2)

Thresholds the image using an adaptive threshold that is computed using a local square region centered on each pixel. The threshold is equal to the average value of the surrounding pixels plus the bias. If down is true then b(x,y) = I(x,y) <= T(x,y) + bias ? 1 : 0. Otherwise b(x,y) = I(x,y) >= T(x,y) + bias ? 0 : 1

NOTE: Internally, images are declared to store intermediate results. If more control is needed over memory call the type specific function.

Parameters:

input - Input image.

output - (optional) Output binary image. If null it will be declared internally.

radius - Radius of square region.

bias - Bias used to adjust threshold

down - Should it threshold up or down.

work1 - (Optional) Internal workspace. Can be null

work2 - (Optional) Internal workspace. Can be null

Returns:

Thresholded image.

adaptiveGaussian

public static <T extends ImageSingleBand> ImageUInt8 adaptiveGaussian(T input,
                                                      ImageUInt8 output,
                                                      int radius,
                                                      double bias,
                                                      boolean down,
                                                      T work1,
                                                      T work2)

Thresholds the image using an adaptive threshold that is computed using a local square region centered on each pixel. The threshold is equal to the gaussian weighted sum of the surrounding pixels plus the bias. If down is true then b(x,y) = I(x,y) <= T(x,y) + bias ? 1 : 0. Otherwise b(x,y) = I(x,y) >= T(x,y) + bias ? 0 : 1

NOTE: Internally, images are declared to store intermediate results. If more control is needed over memory call the type specific function.

Parameters:

input - Input image.

output - (optional) Output binary image. If null it will be declared internally.

radius - Radius of square region.

bias - Bias used to adjust threshold

down - Should it threshold up or down.

work1 - (Optional) Internal workspace. Can be null

work2 - (Optional) Internal workspace. Can be null

Returns:

Thresholded image.