ru.aifgi.recognizer.model.preprosessing.OtsuAlgorithm.java Source code

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Here is the source code for ru.aifgi.recognizer.model.preprosessing.OtsuAlgorithm.java

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package ru.aifgi.recognizer.model.preprosessing;
/*
 * Copyright 2012 Alexey Ivanov
 *
 * 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.
 */

import com.google.common.math.DoubleMath;
import ru.aifgi.recognizer.model.MathUtil;

import java.math.RoundingMode;

/**
 * @author aifgi
 */

public class OtsuAlgorithm {
    private static int[] computeHistogram(final double[][] image) {
        final int[] histogram = new int[256];
        for (final double[] line : image) {
            for (final double value : line) {
                final int brightness = DoubleMath.roundToInt(value, RoundingMode.HALF_UP);
                ++histogram[brightness];
            }
        }
        return histogram;
    }

    public static int thresholding(final double[][] image) {
        final int[] histogram = computeHistogram(image);

        final int length = histogram.length;
        int m = 0;
        int n = 0;
        for (int i = 0; i < length; ++i) {
            final int value = histogram[i];
            m += value;
            n += i * value;
        }

        double maxSigma = Double.MIN_VALUE;
        int threshold = 0;
        int brightnessesNumberSum = 0;
        int brightnessesSum = 0;
        for (int i = 0; i < length; ++i) {
            final int value = histogram[i];
            brightnessesNumberSum += value;
            brightnessesSum += i * value;

            final double probability = brightnessesNumberSum / (double) m;
            final double firstMeanValue = brightnessesSum / (double) brightnessesNumberSum;
            final double secondMeanValue = (n - brightnessesSum) / (double) (m - brightnessesNumberSum);
            final double sigma = probability * (1 - probability) * MathUtil.sqr(firstMeanValue - secondMeanValue);
            if (sigma > maxSigma) {
                maxSigma = sigma;
                threshold = i;
            }
        }
        return threshold;
    }

    private OtsuAlgorithm() {
    }
}