boofcv.alg.background.stationary.BackgroundStationaryGaussian Maven / Gradle / Ivy

Go to download

Show more of this group Show more artifacts with this name
Show all versions of feature Show documentation

BoofCV is an open source Java library for real-time computer vision and robotics applications.

There is a newer version: 0.26

/*
 * Copyright (c) 2011-2015, Peter Abeles. All Rights Reserved.
 *
 * This file is part of BoofCV (http://boofcv.org).
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package boofcv.alg.background.stationary;

import boofcv.alg.background.BackgroundAlgorithmGaussian;
import boofcv.alg.background.BackgroundModelMoving;
import boofcv.alg.background.BackgroundModelStationary;
import boofcv.struct.image.ImageBase;
import boofcv.struct.image.ImageType;

/**
 * Implementation of {@link BackgroundAlgorithmGaussian} for moving images.
 *
 * @see BackgroundAlgorithmGaussian
 * @see BackgroundModelMoving
 *
 * @author Peter Abeles
 */
public abstract class BackgroundStationaryGaussian
		extends BackgroundModelStationary implements BackgroundAlgorithmGaussian
{
	/**
	 * Specifies how fast it will adapt. 0 to 1, inclusive.  0 = static  1.0 = instant.
	 */
	protected float learnRate;

	/**
	 * Threshold for classifying a pixel as background or not. This threshold is applied to the
	 * computed Mahalanobis from the distribution.
	 */
	protected float threshold;

	/**
	 * The initial variance assigned to a new pixel.  Larger values to reduce false positives due to
	 * under sampling
	 */
	protected float initialVariance = Float.MIN_VALUE;

	protected float minimumDifference = 0;

	/**
	 * See class documentation for parameters definitions.
	 * @param learnRate Specifies how quickly the background is updated Try 0.05
	 * @param threshold Threshold for background.  ≥ 0.  Try 10
	 * @param imageType Type of input image
	 */
	public BackgroundStationaryGaussian(float learnRate, float threshold,ImageType imageType) {
		super(imageType);

		if( threshold < 0 )
			throw new IllegalArgumentException("Threshold must be more than 0");

		this.learnRate = learnRate;
		this.threshold = threshold;
	}

	@Override
	public float getInitialVariance() {
		return initialVariance;
	}

	@Override
	public void setInitialVariance(float initialVariance) {
		this.initialVariance = initialVariance;
	}

	@Override
	public float getLearnRate() {
		return learnRate;
	}

	@Override
	public void setLearnRate(float learnRate) {
		this.learnRate = learnRate;
	}

	@Override
	public float getThreshold() {
		return threshold;
	}

	@Override
	public void setThreshold(float threshold) {
		this.threshold = threshold;
	}

	@Override
	public float getMinimumDifference() {
		return minimumDifference;
	}

	@Override
	public void setMinimumDifference(float minimumDifference) {
		this.minimumDifference = minimumDifference;
	}
}