Road Extraction from image

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Java

image-processing

i am doing project of final year in that i Extract road from image .in that i take image , image can be segment into three different cluster by using k-means clustering algorithm that image divide into three different cluster after i tried to select longest connected component cluster from that image but not getting what i want .i want to delete all the portion from that image (Except Road)or want to visible only road from that image . how can do that
o input image
o output image
o Expected Output

import java.awt.Color;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;

import javax.imageio.ImageIO;

public class Kmeans1 {
	BufferedImage image_temp;
	boolean not_terminated;
	int loops, changedPixels;
	int[] histogram;
	static int count = 0;
	int[] lowerbounds = new int[3];
	static int g = 0;
	int[] lb = new int[3];
	int[] ub = new int[3];
	int[] mean = new int[3];
	BufferedImage imaged;
	BufferedImage thresholdimage, dilateimage;

	public Kmeans1(BufferedImage image, int bins, int[] histogram)
			throws IOException {
		this.histogram = histogram;
		initialize(image, bins);
		calcbounds();

		// / calculateMean(histogram);
		processImage(image, bins);
		imaged = returnimage();
		imageWrite();
		for (int j = 0; j < 3; j++) {
			System.out.println("LB" + j + "=" + lb[j] + " UB" + j + "=" + ub[j]
					+ " Means" + j + "=" + mean[j]);
		}
	}

	public void initialize(BufferedImage image, int bins) {
		image_temp = image;
		not_terminated = true;
		mean[0] = 173;
		mean[1] = 100;
		mean[2] = 112;
	}

	public int createmean(BufferedImage image, int i, int bins) {
		int pixelindex = 0;
		int sum = 0;
		int value = 0;
		for (int h = 0; h < image.getHeight(); h++) {
			for (int w = 0; w < image.getWidth(); w++) {
				try {
					pixelindex += 1;
					if (pixelindex % bins == i) {
						Color rgb = new Color(image.getRGB(w, h));
						sum += rgb.getRed();
						value += 1;
						count++;
					}
				} catch (Exception e) {
					// TODO Auto-generated catch block
					e.printStackTrace();
				}
			}
		}
		return sum / value;

	}

	public void calcbounds() {
		for (int j = 0; j < 3; j++) {
			int lb1 = calculatelb(j);
			int ub1 = calculateub(j);
			lowerbounds[j] = lb1;
			lb[j] = lb1;
			ub[j] = ub1;
		}

	}

	private int calculatelb(int index) {
		int cMean = mean[index];
		int currentBound = 0;
		for (int i = 0; i < 3; i++) {
			if (cMean > mean[i]) {
				currentBound = Math.max((cMean + mean[i]) / 2, currentBound);
			} else {
			}
		}
		return currentBound;
	}

	private int calculateub(int index) {
		int cMean = mean[index];
		int currentBound = 255;
		for (int i = 0; i < 3; i++) {
			if (cMean < mean[i]) {
				currentBound = Math.min((cMean + mean[i]) / 2, currentBound);
			} else {
			}
		}
		return currentBound;
	}

	private void processImage(BufferedImage image, int bins) {
		int delta = 255 / (bins - 1);

		for (int h = 0; h < image.getHeight(); h++) {
			for (int w = 0; w < image.getWidth(); w++)

			{
				Color rgb = new Color(image.getRGB(w, h));
				int grey = rgb.getRed();

				for (int i = 0; i < 3; i++) {
					if (grey > lb[i] && grey < ub[i]) {
						g = i * delta;
						image_temp.setRGB(w, h, (new Color(g, g, g)).getRGB());
					} else {
						image_temp.setRGB(w, h, (new Color(g, g, g)).getRGB());
					}
				}
			}
		}
	}

	public BufferedImage returnimage() {
		return image_temp;
	}

	// BufferedImage img1=image_temp;
	public void imageWrite() throws IOException {
		// BufferedImage img1=image_temp;
		ImageIO.write(imaged, "jpg", new File("output.jpg"));
		System.out.println("image write completed");
	}

}
</code>
main method
<code> //
import java.awt.Color;
import java.awt.image.BufferedImage;
import java.awt.image.Kernel;
import java.awt.image.ConvolveOp;
import java.io.File;
import java.io.IOException;

import javax.imageio.ImageIO;

public class design1 {
	static BufferedImage image;
	static int[] histogram = new int[256];

	public void makeHistogram() throws IOException {
		image = ImageIO.read(new File("input.png"));
		for (int i = 0; i < 256; i++)
			histogram[i] = 0;
		for (int h = 0; h < image.getHeight(); h++) {
			for (int w = 0; w < image.getWidth(); w++) {
				Color color = new Color(image.getRGB(w, h));
				int greyvalue = color.getRed();
				histogram[greyvalue] += 1;
			}
		}
	}

	public static void main(String[] args) throws IOException {

		new Kmeans1(image, 3, histogram);
	}

}