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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.convolution;
31  
32  import org.openimaj.image.FImage;
33  import org.openimaj.image.processor.SinglebandKernelProcessor;
34  
35  /**
36   * Apply the sobel operator to an image. This is achieved using a kernel convolution in the X and Y. 
37   * The kernels are normalised 3x3 first derivatives of a gaussian of sigma 1.0f
38   * 
39   * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
40   * @author Sina Samangooei (ss@ecs.soton.ac.uk)
41   *
42   */
43  public class FSobelMagnitude implements SinglebandKernelProcessor<Float, FImage> {
44  
45  	/**
46  	 * The 3x3 derivative of a gaussian of sigma 1 in the x direction
47  	 */
48  	public static final FImage KERNEL_X = new FImage(new float[][] {
49  			{1,0,-1},
50  			{2,0,-2},
51  			{1,0,-1}	
52  	});
53  
54  	/**
55  	 * The 3x3 derivative of a gaussian of sigma 1 in the x direction
56  	 */
57  	public static final FImage KERNEL_Y = new FImage(new float[][] {
58  			{ 1, 2, 1},
59  			{ 0, 0, 0},
60  			{-1,-2,-1}
61  	});
62  
63  	@Override
64  	public int getKernelHeight() {
65  		return 3;
66  	}
67  
68  	@Override
69  	public int getKernelWidth() {
70  		return 3;
71  	}
72  
73  	@Override
74  	public Float processKernel(FImage patch) {
75  		float sumx=0, sumy=0;
76  
77  		for (int r=0; r<3; r++) {
78  			for (int c=0; c<3; c++) {
79  				sumx += (KERNEL_X.pixels[2-r][2-c] * patch.pixels[r][c]);
80  				sumy += (KERNEL_Y.pixels[2-r][2-c] * patch.pixels[r][c]);
81  			}
82  		}
83  
84  		return (float)Math.sqrt((sumx*sumx) + (sumy*sumy));
85  	}	
86  }