boofcv.abst.feature.detect.line.HoughGradient_to_DetectLine Maven / Gradle / Ivy

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BoofCV is an open source Java library for real-time computer vision and robotics applications.
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/*
 * Copyright (c) 2011-2019, 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.abst.feature.detect.line;

import boofcv.abst.filter.derivative.ImageGradient;
import boofcv.alg.feature.detect.edge.GGradientToEdgeFeatures;
import boofcv.alg.feature.detect.line.HoughTransformGradient;
import boofcv.alg.filter.binary.ThresholdImageOps;
import boofcv.alg.filter.derivative.GImageDerivativeOps;
import boofcv.core.image.GeneralizedImageOps;
import boofcv.factory.filter.derivative.FactoryDerivative;
import boofcv.struct.image.GrayF32;
import boofcv.struct.image.GrayU8;
import boofcv.struct.image.ImageGray;
import boofcv.struct.image.ImageType;
import georegression.struct.line.LineParametric2D_F32;

import java.util.List;

/**
 * Converts {@link HoughTransformGradient} into {@link DetectLine}
 *
 * 
 * USAGE NOTES: Blurring the image prior to processing can often improve performance.
 * Results will not be perfect and to detect all the obvious lines in the image several false
 * positives might be returned.
 * 
 *
 * @see HoughTransformGradient
 * @see boofcv.alg.feature.detect.line.HoughParametersFootOfNorm
 *
 * @author Peter Abeles
 */
public class HoughGradient_to_DetectLine, D extends ImageGray>
	implements DetectLine
{
	HoughTransformGradient hough;
	// computes image gradient
	ImageGradient gradient;
	D derivX, derivY;

	// storage for gradient intensity image
	GrayF32 edgeIntensity = new GrayF32(1,1);
	GrayF32 suppressed = new GrayF32(1,1);
	// storage for edge binary image
	GrayU8 binary = new GrayU8(1,1);

	// threshold for intensity image
	float thresholdEdge = 20;

	// should it apply non-max or not
	boolean nonMaxSuppression=true;

	Class inputType;
	Class derivType;

	public HoughGradient_to_DetectLine( HoughTransformGradient hough, ImageGradient gradient,
										Class inputType ) {
		this.hough = hough;
		this.gradient = gradient;
		this.inputType = inputType;
		this.derivType = GImageDerivativeOps.getDerivativeType(inputType);

		derivX = GeneralizedImageOps.createSingleBand(derivType,1,1);
		derivY = GeneralizedImageOps.createSingleBand(derivType,1,1);
	}
	public HoughGradient_to_DetectLine( HoughTransformGradient hough,  Class inputType ) {
		this(hough, FactoryDerivative.prewitt(inputType,(Class)null), inputType);
	}

	@Override
	public List detect(I input) {
		gradient.process(input,derivX,derivY);
		GGradientToEdgeFeatures.intensityAbs(derivX, derivY, edgeIntensity);
		if( nonMaxSuppression ) {
			GGradientToEdgeFeatures.nonMaxSuppressionCrude4(edgeIntensity, derivX, derivY, suppressed);
			ThresholdImageOps.threshold(suppressed, binary, thresholdEdge, false);
		} else {
			ThresholdImageOps.threshold(edgeIntensity, binary, thresholdEdge, false);
		}

		hough.transform(derivX,derivY,binary);

		return hough.getLinesMerged();
	}

	@Override
	public ImageType getInputType() {
		return ImageType.single(inputType);
	}

	public float getThresholdEdge() {
		return thresholdEdge;
	}

	public void setThresholdEdge(float thresholdEdge) {
		this.thresholdEdge = thresholdEdge;
	}

	public GrayF32 getEdgeIntensity() {
		return edgeIntensity;
	}

	public GrayU8 getBinary() {
		return binary;
	}

	public HoughTransformGradient getHough() {
		return hough;
	}

	public ImageGradient getGradient() {
		return gradient;
	}

	public D getDerivX() {
		return derivX;
	}

	public D getDerivY() {
		return derivY;
	}

	public boolean isNonMaxSuppression() {
		return nonMaxSuppression;
	}

	public void setNonMaxSuppression(boolean nonMaxSuppression) {
		this.nonMaxSuppression = nonMaxSuppression;
	}
}