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BoofCV is an open source Java library for real-time computer vision and robotics applications.
There is a newer version: 1.1.7
/*
 * Copyright (c) 2011-2017, 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.intensity;

import boofcv.struct.QueueCorner;
import boofcv.struct.image.GrayF32;
import boofcv.struct.image.ImageGray;

/**
 * Extracts corners from a the image and or its gradient.  This is a generalized interface and lacks some of the functionality
 * of more specialized classes.
 *
 * @see boofcv.alg.feature.detect.intensity.FeatureIntensity
 * @see boofcv.abst.feature.detect.extract.NonMaxSuppression
 *
 * @param  Input image type.
 * @param  Image derivative type.
 *
 * @author Peter Abeles
 */

public interface GeneralFeatureIntensity,D extends ImageGray> {

	/**
	 * Computes the corner's intensity.  Before computing the various image derivatives call
	 * {@link #getRequiresGradient()} and {@link #getRequiresHessian()} to see if they are needed.
	 *
	 * @param image Original input image
	 * @param derivX First derivative x-axis
	 * @param derivY First derivative x-axis
	 * @param derivXX Second derivative x-axis x-axis
	 * @param derivYY Second derivative x-axis y-axis
	 * @param derivXY Second derivative x-axis y-axis
	 *
	 */
	public void process( I image , D derivX , D derivY , D derivXX , D derivYY , D derivXY );

	/**
	 * Returns an image containing an intensity mapping showing how corner like each pixel is.
	 * Unprocessed image borders will have a value of zero.
	 *
	 * @return Corner intensity image.
	 */
	public GrayF32 getIntensity();

	/**
	 * (Optional) Returns a list of candidate for local minimums.
	 *
	 * @return List of potential features.  If not supported then null is returned.
	 */
	public QueueCorner getCandidatesMin();

	/**
	 *  (Optional) Returns a list of candidate for local maximums.
	 *
	 * @return List of potential features.  If not supported then null is returned.
	 */
	public QueueCorner getCandidatesMax();

	/**
	 * If the image gradient is required for calculations.
	 *
	 * @return true if the image gradient is required.
	 */
	public boolean getRequiresGradient();

	/**
	 * Is the image's second derivative required?
	 *
	 * @return is the hessian required.
	 */
	public boolean getRequiresHessian();

	/**
	 * If true there is a list of candidate corners for minimums and/or maximums.
	 */
	public boolean hasCandidates();

	/**
	 * Pixels within this distance from the image border are not processed.
	 *
	 * @return Size of unprocessed border around the image.
	 */
	public int getIgnoreBorder();

	/**
	 * Indicates if local minimums are features or not.
	 *
	 * @return true for local minimum features.
	 */
	public boolean localMinimums();

	/**
	 * Indicates if local maximums are features or not.
	 *
	 * @return true for local maximum features.
	 */
	public boolean localMaximums();
}