// Catalano Imaging Library
// The Catalano Framework
//
// Copyright © Diego Catalano, 2012-2016
// diego.catalano at live.com
//
// This library is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 2.1 of the License, or (at your option) any later version.
//
// This library is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
// Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License along with this library; if not, write to the Free Software
// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
//
package Catalano.Imaging.Texture.BinaryPattern;
import Catalano.Imaging.FastBitmap;
import Catalano.Imaging.Tools.ImageHistogram;
/**
* Weber binary patterns (WBP) is a type of feature used for classification in computer vision.
* WBP was first described in 2015. It has since been found to be a powerful feature for texture classification.
*
* @author Diego Catalano
*/
public class WeberBinaryPattern implements IBinaryPattern{
private double threshold;
/**
* Get threshold.
* @return Threshold value.
*/
public double getThreshold() {
return threshold;
}
/**
* Set threshold.
* @param threshold Threshold value.
*/
public void setThreshold(double threshold) {
this.threshold = threshold;
}
/**
* Initialize a new instance of the WeberBinaryPattern class.
* Default threshold: -0.2
*/
public WeberBinaryPattern() {
this(-0.2);
}
/**
* Initialize a new instance of the WeberBinaryPattern class.
* @param threshold Threshold.
*/
public WeberBinaryPattern(double threshold) {
this.threshold = threshold;
}
@Override
public ImageHistogram ComputeFeatures(FastBitmap fastBitmap) {
if (!fastBitmap.isGrayscale())
throw new IllegalArgumentException("WBP works only with grayscale images.");
int width = fastBitmap.getWidth() - 1;
int height = fastBitmap.getHeight() - 1;
int sum;
int[] g = new int[256];
double cp;
for (int x = 1; x < height; x++) {
for (int y = 1; y < width; y++) {
cp = fastBitmap.getGray(x, y);
sum = 0;
if (((fastBitmap.getGray(x - 1, y - 1) - cp) / cp) > threshold) sum += 128;
if (((fastBitmap.getGray(x - 1, y) - cp) / cp) > threshold) sum += 64;
if (((fastBitmap.getGray(x - 1, y + 1) - cp) / cp) > threshold) sum += 32;
if (((fastBitmap.getGray(x, y + 1) - cp) / cp) > threshold) sum += 16;
if (((fastBitmap.getGray(x + 1, y + 1) - cp) / cp) > threshold) sum += 8;
if (((fastBitmap.getGray(x + 1, y) - cp) / cp) > threshold) sum += 4;
if (((fastBitmap.getGray(x + 1, y - 1) - cp) / cp) > threshold) sum += 2;
if (((fastBitmap.getGray(x, y - 1) - cp) / cp) > threshold) sum += 1;
g[sum]++;
}
}
return new ImageHistogram(g);
}
}
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