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1   /**
2    * Copyright (c) 2011, The University of Southampton and the individual contributors.
3    * All rights reserved.
4    *
5    * Redistribution and use in source and binary forms, with or without modification,
6    * are permitted provided that the following conditions are met:
7    *
8    *   * 	Redistributions of source code must retain the above copyright notice,
9    * 	this list of conditions and the following disclaimer.
10   *
11   *   *	Redistributions in binary form must reproduce the above copyright notice,
12   * 	this list of conditions and the following disclaimer in the documentation
13   * 	and/or other materials provided with the distribution.
14   *
15   *   *	Neither the name of the University of Southampton nor the names of its
16   * 	contributors may be used to endorse or promote products derived from this
17   * 	software without specific prior written permission.
18   *
19   * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
20   * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
21   * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
22   * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
23   * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
24   * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
25   * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
26   * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
27   * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
28   * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
29   */
30  package org.openimaj.image.processing.threshold;
31  
32  import org.openimaj.image.FImage;
33  import org.openimaj.image.processing.convolution.FGaussianConvolve;
34  import org.openimaj.image.processor.SinglebandImageProcessor;
35  
36  /**
37   * Adaptive local thresholding using the Gaussian weighted sum of the patch and
38   * an offset.
39   * 
40   * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
41   * 
42   */
43  public class AdaptiveLocalThresholdGaussian implements SinglebandImageProcessor<Float, FImage> {
44  	private float offset;
45  	private float sigma;
46  
47  	/**
48  	 * Construct the thresholding operator with the given Gaussian standard
49  	 * deviation, sigma, and offset
50  	 * 
51  	 * @param sigma
52  	 *            Gaussian kernel standard deviation
53  	 * @param offset
54  	 *            offset from the patch mean at which the threshold occurs
55  	 */
56  	public AdaptiveLocalThresholdGaussian(float sigma, float offset) {
57  		this.sigma = sigma;
58  		this.offset = offset;
59  	}
60  
61  	@Override
62  	public void processImage(FImage image) {
63  		final FImage tmp = image.process(new FGaussianConvolve(sigma));
64  
65  		final float[][] tpix = tmp.pixels;
66  		final float[][] ipix = image.pixels;
67  		for (int y = 0; y < image.height; y++)
68  			for (int x = 0; x < image.width; x++)
69  				tpix[y][x] = ipix[y][x] < (tpix[y][x] - offset) ? 0f : 1f;
70  
71  		image.internalAssign(tmp);
72  	}
73  }