org.opencv.video

Class BackgroundSubtractor

java.lang.Object

org.opencv.core.Algorithm

org.opencv.video.BackgroundSubtractor

Direct Known Subclasses:

BackgroundSubtractorCNT, BackgroundSubtractorGMG, BackgroundSubtractorGSOC, BackgroundSubtractorKNN, BackgroundSubtractorLSBP, BackgroundSubtractorMOG, BackgroundSubtractorMOG2

public class BackgroundSubtractor
extends Algorithm

Base class for background/foreground segmentation. : The class is only used to define the common interface for the whole family of background/foreground segmentation algorithms.

Field Summary

Fields inherited from class org.opencv.core.Algorithm

nativeObj

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	BackgroundSubtractor(long addr)

Method Summary

Modifier and Type	Method and Description
static BackgroundSubtractor	__fromPtr__(long addr)
void	apply(Mat image, Mat fgmask) Computes a foreground mask.
void	apply(Mat image, Mat fgmask, double learningRate) Computes a foreground mask.
protected void	finalize()
void	getBackgroundImage(Mat backgroundImage) Computes a background image.

Methods inherited from class org.opencv.core.Algorithm

clear, empty, getDefaultName, getNativeObjAddr, save

Methods inherited from class java.lang.Object

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

Constructor Detail

BackgroundSubtractor

protected BackgroundSubtractor(long addr)

Method Detail

__fromPtr__

public static BackgroundSubtractor __fromPtr__(long addr)

apply

public void apply(Mat image,
                  Mat fgmask,
                  double learningRate)

Computes a foreground mask.

Parameters:

image - Next video frame.

fgmask - The output foreground mask as an 8-bit binary image.

learningRate - The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame.

apply

public void apply(Mat image,
                  Mat fgmask)

Computes a foreground mask.

Parameters:

image - Next video frame.

fgmask - The output foreground mask as an 8-bit binary image. learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame.

getBackgroundImage

public void getBackgroundImage(Mat backgroundImage)

Computes a background image.

Parameters:

backgroundImage - The output background image. Note: Sometimes the background image can be very blurry, as it contain the average background statistics.

finalize

protected void finalize()
                 throws Throwable

Overrides:

finalize in class Algorithm

Throws:

Throwable