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How can i identify/count how many objects are there in a image that has overlaps

The problem is I am trying to identify plants from a drone image. The plants from the image contain overlaps and are of different shapes/sizes. I am unsure of where to look or what types of methods to use for this and am looking for suggestions.
I have taken snippets from a full image of the fields and attempted to: Use Convolusion Neural Networks to train a xml file that was used in a java program, Used convulsion 3x3 matrixes such as sharpen and edge detection (specifically focused around Sobel and Laplace), identify each plant by taking their RGB values and greying out all others. I have focused efforts on the 3rd method of identifying their individual RGB values however this is difficult due to all of them having different values.
This is the current code I use to scan and remove irrelevant RGB values:
I only store red and blue because a funny thing is, the green values of plants and that of background are actually nearly identical.
Here is a image of the field:
I also have a few other images of the ways I have tried so far:
The result of using sobel operator
//important data
int pixX = 330; //resolution of image
int pixY = 370;
int pixT = pixX * pixY; //total amount of pixels
int xloc = 0;//used to locate pixels to remove
int yloc = 0;
File test = new File("FILE.png)
int x = 0, y = 0; //Current XY values
int colorsplit[][] = new int[2][pixT];//obtaining red and blue will be stored in this 2d array
try {
for (int c = 0; c < pixT - 1; c=c+2) { //I use C+2 to jump 2 pixels to make the process faster
BufferedImage image = ImageIO.read(test);//buffered image read
int clr = image.getRGB(x, y); //getting values as binary(? i think)
int red = (clr & 0x00ff0000) >> 16; //bit shifting for red values
int blue = clr & 0x000000ff; //Blue values
for (int n = 0; n < 4; n++) { // this is used to store values so that a single run will store the same value twice for 2 pixels side by side (efficiency measures)
switch (n) {//switch to store Red Blue codes
case 0:
colorsplit[0][c] = red;//store
break;
case 1:
colorsplit[1][c] = blue;//store
break;
case 2:
colorsplit[0][c + 1] = red;//store
break;
case 3:
colorsplit[1][c + 1] = blue;//store
}
}//END switch
x = x + 2;
if (x == pixX) {//Going up in XY values to cover all values
x = 0;
y++;
}//end if
}//end for
...//end of try, catch IOException
for (int c = 0; c < pixT; c++) { //Starting to identify redundant pixels
if (colorsplit[0][c] > 200 || colorsplit[1][c] > 100) { //parameters of redundant pixels
xloc = c % pixX;
yloc = c / pixX;//locating XY pixels
image.setRGB(xloc, yloc, 0); //Setting redundant pixels to black
System.out.println(xloc + "," + yloc + " setted"); //confirmation text
}//end for
//end
I do not get many errors however the problem lies more with the program not working as intended.
Edit: Turns out most things were fine, but one thing I didn't do was combine multiple identification programs. Ended up doing RGB reduction to only get R values followed by a Sobel operator and then using pixel by pixel analysis to filter out the redundant pixels.

Java Convolution

Hi I am in need of some help. I need to write a convolution method from scratch that takes in the following inputs: int[][] and BufferedImage inputImage. I can assume that the kernel has size 3x3.
My approach is to do the follow:
convolve inner pixels
convolve corner pixels
convolve outer pixels
In the program that I will post below I believe I convolve the inner pixels but I am a bit lost at how to convolve the corner and outer pixels. I am aware that corner pixels are at (0,0), (width-1,0), (0, height-1) and (width-1,height-1). I think I know to how approach the problem but not sure how to execute that in writing though. Please to aware that I am very new to programming :/ Any assistance will be very helpful to me.
import java.awt.*;
import java.awt.image.BufferedImage;
import com.programwithjava.basic.DrawingKit;
import java.util.Scanner;
public class Problem28 {
// maximum value of a sample
private static final int MAX_VALUE = 255;
//minimum value of a sample
private static final int MIN_VALUE = 0;
public BufferedImage convolve(int[][] kernel, BufferedImage inputImage) {
}
public BufferedImage convolveInner(double center, BufferedImage inputImage) {
int width = inputImage.getWidth();
int height = inputImage.getHeight();
BufferedImage inputImage1 = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
//inner pixels
for (int x = 1; x < width - 1; x++) {
for (int y = 1; y < height - 1; y ++) {
//get pixels at x, y
int colorValue = inputImage.getRGB(x, y);
Color pixelColor = new Color(colorValue);
int red = pixelColor.getRed() ;
int green = pixelColor.getGreen() ;
int blue = pixelColor.getBlue();
int innerred = (int) center*red;
int innergreen = (int) center*green;
int innerblue = (int) center*blue;
Color newPixelColor = new Color(innerred, innergreen, innerblue);
int newRgbvalue = newPixelColor.getRGB();
inputImage1.setRGB(x, y, newRgbvalue);
}
}
return inputImage1;
}
public BufferedImage convolveEdge(double edge, BufferedImage inputImage) {
int width = inputImage.getWidth();
int height = inputImage.getHeight();
BufferedImage inputImage2 = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
//inner pixels
for (int x = 0; x < width - 1; x++) {
for (int y = 0; y < height - 1; y ++) {
//get pixels at x, y
int colorValue = inputImage.getRGB(x, y);
Color pixelColor = new Color(colorValue);
int red = pixelColor.getRed() ;
int green = pixelColor.getGreen() ;
int blue = pixelColor.getBlue();
int innerred = (int) edge*red;
int innergreen = (int) edge*green;
int innerblue = (int) edge*blue;
Color newPixelColor = new Color(innerred, innergreen, innerblue);
int newRgbvalue = newPixelColor.getRGB();
inputImage2.setRGB(x, y, newRgbvalue);
}
}
return inputImage2;
}
public BufferedImage convolveCorner(double corner, BufferedImage inputImage) {
int width = inputImage.getWidth();
int height = inputImage.getHeight();
BufferedImage inputImage3 = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
//inner pixels
for (int x = 0; x < width - 1; x++) {
for (int y = 0; y < height - 1; y ++) {
//get pixels at x, y
int colorValue = inputImage.getRGB(x, y);
Color pixelColor = new Color(colorValue);
int red = pixelColor.getRed() ;
int green = pixelColor.getGreen() ;
int blue = pixelColor.getBlue();
int innerred = (int) corner*red;
int innergreen = (int) corner*green;
int innerblue = (int) corner*blue;
Color newPixelColor = new Color(innerred, innergreen, innerblue);
int newRgbvalue = newPixelColor.getRGB();
inputImage3.setRGB(x, y, newRgbvalue);
}
}
return inputImage3;
}
public static void main(String[] args) {
DrawingKit dk = new DrawingKit("Compositor", 1000, 1000);
BufferedImage p1 = dk.loadPicture("image/pattern1.jpg");
Problem28 c = new Problem28();
BufferedImage p5 = c.convolve();
dk.drawPicture(p5, 0, 100);
}
}
I changed the code a bit but the output comes out as black. What did I do wrong:
import java.awt.*;
import java.awt.image.BufferedImage;
import com.programwithjava.basic.DrawingKit;
import java.util.Scanner;
public class Problem28 {
// maximum value of a sample
private static final int MAX_VALUE = 255;
//minimum value of a sample
private static final int MIN_VALUE = 0;
public BufferedImage convolve(int[][] kernel, BufferedImage inputImage) {
int width = inputImage.getWidth();
int height = inputImage.getHeight();
BufferedImage inputImage1 = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
//for every pixel
for (int x = 0; x < width; x ++) {
for (int y = 0; y < height; y ++) {
int colorValue = inputImage.getRGB(x,y);
Color pixelColor = new Color(colorValue);
int red = pixelColor.getRed();
int green = pixelColor.getGreen();
int blue = pixelColor.getBlue();
double gray = 0;
//multiply every value of kernel with corresponding image pixel
for (int i = 0; i < 3; i ++) {
for (int j = 0; j < 3; j ++) {
int imageX = (x - 3/2 + i + width) % width;
int imageY = (x -3/2 + j + height) % height;
int RGB = inputImage.getRGB(imageX, imageY);
int GRAY = (RGB) & 0xff;
gray += (GRAY*kernel[i][j]);
}
}
int out;
out = (int) Math.min(Math.max(gray * 1, 0), 255);
inputImage1.setRGB(x, y, new Color(out,out,out).getRGB());
}
}
return inputImage1;
}
public static void main(String[] args) {
int[][] newArray = {{1/9, 1/9, 1/9}, {1/9, 1/9, 1/9}, {1/9, 1/9, 1/9}};
DrawingKit dk = new DrawingKit("Problem28", 1000, 1000);
BufferedImage p1 = dk.loadPicture("image/pattern1.jpg");
Problem28 c = new Problem28();
BufferedImage p2 = c.convolve(newArray, p1);
dk.drawPicture(p2, 0, 100);
}
}

Welcome ewuzz! I wrote a convolution using CUDA about a week ago, and the majority of my experience is with Java, so I feel qualified to provide advice for this problem.
Rather than writing all of the code for you, the best way to solve this large program is to discuss individual elements. You mentioned you are very new to programming. As the programs you write become more complex, it's essential to write small working snippets before combining them into a large successful program (or iteratively add snippets). With this being said, it's already apparent you're trying to debug a ~100 line program, and this approach will cost you time in most cases.
The first point to discuss is the general approach you mentioned. If you think about the program, what is the simplest and most repeated step? Obviously this is the kernel/mask step, so we can start from here. When you convolute each pixel, you are performing a similar option, regardless of the position (corner, edge, inside). While there are special steps necessary for these edge cases, they share similar underlying steps. If you try to write code for each of these cases separately, you will have to update the code in multiple (three) places with each adjustment and it will make the whole program more difficult to grasp.
To support my point above, here's what happened when I pasted your code into IntelliJ. This illustrates the (yellow) red flag of using the same code in multiple places:
The concrete way to fix this problem is to combine the three convolve methods into a single one and use if statements for edge-cases as necessary.
Our pseudocode with this change:
convolve(kernel, inputImage)
for each pixel in the image
convolve the single pixel and check edge cases
endfor
end
That seems pretty basic right? If we are able to successfully check edge cases, then this extremely simple logic will work. The reason I left it so general above to show how convolve the single pixel and check edge cases is logically grouped. This means it's a good candidate for extracting a method, which could look like:
private void convolvePixel(int x, int y, int[][] kernel, BufferedImage input, BufferedImage output)
Now to implement our method above, we will need to break it into a few steps, which we may then break into more steps if necessary. We'll need to look at the input image, if possible for each pixel accumulate the values using the kernel, and then set this in the output image. For brevity I will only write pseudocode from here.
convolvePixel(x, y, kernel, input, output)
accumulation = 0
for each row of kernel applicable pixels
for each column of kernel applicable pixels
if this neighboring pixel location is within the image boundaries then
input color = get the color at this neighboring pixel
adjusted value = input color * relative kernel mask value
accumulation += adjusted value
else
//handle this somehow, mentioned below
endif
endfor
endfor
set output pixel as accumulation, assuming this convolution method does not require normalization
end
The pseudocode above is already relatively long. When implementing you could write methods for the if and the else cases, but it you should be fine with this structure.
There are a few ways to handle the edge case of the else above. Your assignment probably specifies a requirement, but the fancy way is to tile around, and pretend like there's another instance of the same image next to this input image. Wikipedia explains three possibilities:
Extend - The nearest border pixels are conceptually extended as far as necessary to provide values for the convolution. Corner pixels are extended in 90° wedges. Other edge pixels are extended in lines.
Wrap - (The method I mentioned) The image is conceptually wrapped (or tiled) and values are taken from the opposite edge or corner.
Crop - Any pixel in the output image which would require values from beyond the edge is skipped. This method can result in the output image being slightly smaller, with the edges having been cropped.
A huge part of becoming a successful programmer is researching on your own. If you read about these methods, work through them on paper, run your convolvePixel method on single pixels, and compare the output to your results by hand, you will find success.
Summary:
Start by cleaning-up your code before anything.
Group the same code into one place.
Hammer out a small chunk (convolving a single pixel). Print out the result and the input values and verify they are correct.
Draw out edge/corner cases.
Read about ways to solve edge cases and decide what fits your needs.
Try implementing the else case through the same form of testing.
Call your convolveImage method with the loop, using the convolvePixel method you know works. Done!
You can look up pseudocode and even specific code to solve the exact problem, so I focused on providing general insight and strategies I have developed through my degree and personal experience. Good luck and please let me know if you want to discuss anything else in the comments below.
Java code for multiple blurs via convolution.

Detect & remove a range of colors from Java BufferedImage

I'm building an application that uses OCR to read text from an image (using Tess4J for Google's Tesseract), but I want to ignore the tan-colored text and only read the grey.
In the image below, for instance, I only want to read "Ricki" and ignore "AOA".
http://i.imgur.com/daCuTbB.png
To accomplish this, I figured removing the tan color from the image before performing OCR was my best option.
/* Remove RGB Value for Group Tag */
int width = image.getWidth();
int height = image.getHeight();
int[] pixels = new int[width * height];
image.getRGB(0, 0, width, height, pixels, 0, width);
for (int i = 0; i < pixels.length; i++) {
//If pixel is between dark-tan value and light-tan value
if (pixels[i] > 0xFF57513b && pixels[i] < 0xFF6b6145) {
// Set pixel to black
System.out.println("pixel found");
pixels[i] = 0xFF000000;
}
}
image.setRGB(0, 0, width, height, pixels, 0, width);
But this code removes almost all of the grey text as well. You aren't able to simply compare hex color values for a range of values the way I have. Is there another way to approach detecting a range of colors? Or a better different approach to this problem?

haraldK pointed me in the right direction by mentioning converting RGB. Bit shifting to get individual r, g, and b int values from the hex value allowed me to compare the color within a range and black out a range of colors from the image.
int baser = 108; //base red
int baseg = 96; //base green
int baseb = 68; //base blue
int range = 10; //threshold + and - from base values
/* Set all pixels within +- range of base RGB to black */
for (int i = 0; i < pixels.length; i++) {
int a = (pixels[i]>>24) &0xFF; //alpha
int r = (pixels[i]>>16) &0xFF; //red
int g = (pixels[i]>>8) &0xFF; //green
int b = (pixels[i]>>0) &0xFF; //blue
if ( (r > baser-range && r < baser+range) &&
(g > baseg-range && g < baseg+range) &&
(b > baseb-range && b < baseb+range) ) {
pixels[i] = 0xFF000000; //Set to black
}
}

Update image pixels faster

I am making an image editing like program, and when I want to edit large images it really starts to slow down. What is a good way to edit large image quickly? This example adjusts the image's brightness, it works, but when I get large images such as 3456x2304 its really slow.
I have a slider, which calls this function every time it moves.
// Slider in a dialog box
private void sldBrightnessStateChanged(javax.swing.event.ChangeEvent evt) {
// Get the position of the slider
int val = sldBrightness.getValue();
// Set the text in the textbox
txtBrightness.setText("" + val);
// New Brightness class (see below)
Brightness adjustment = new Brightness();
adjustment.amount(val);
adjustment.applyFilter();
// get the result built by applyFilter();
Canvas.preview = Preview.getImage();
// Update main program
this.getParent().repaint();
}
Then the filter:
package pocketshop.graphics.adjustments;
import java.awt.image.BufferedImage;
import pocketshop.Canvas;
import pocketshop.graphics.Colors;
import pocketshop.graphics.Preview;
public class Brightness{
protected int amount = 0;
public void amount(int amount){
this.amount = amount;
}
public void applyFilter(){
int width = Canvas.image.getWidth();
int height = Canvas.image.getHeight();
int[] pixels = new int[width * height];
Canvas.image.getRGB(0, 0, width, height, pixels, 0, width);
for(int i = 0; i < pixels.length; i++){
int pixel = pixels[i];
//int pixel = Canvas.image.getRGB(x, y);
int red = Colors.red(pixel);
int green = Colors.green(pixel);
int blue = Colors.blue(pixel);
red += amount;
if(red > 255){
red = 255;
}else if(red < 0){
red = 0;
}
green += amount;
if(green > 255){
green = 255;
}else if(green < 0){
green = 0;
}
blue += amount;
if(blue > 255){
blue = 255;
}else if(blue < 0){
blue = 0;
}
pixels[i] = Colors.rgba(red, green, blue);
}
//BrightnessContrastDialog.preview.setRGB(0, 0, width, height, pixels, 0, width);
BufferedImage img = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
img.setRGB(0, 0, width, height, pixels, 0, width);
Preview.setImage(img);
}
}

I have a slider, which calls this function every time it moves.
Don't adjust the image until the slider stops moving. I don't know Swing, but I'm betting there is a test for evt which says whether it is moving or has stopped.
The way you have it, applyFilter may be called 100 times or more as the slider is moved.

As I understand the picture is presented for user in order to give immediate feedback of changes that are made, what you can do us display downsampled version of picture and perform the brightness change to it while slider is moving which will be fast. Once user is satisfied with the value she selected using slider you can apply the change to original image. You can add apply button or something

I would suggest that you investigate OpenCL and its Java binding, JOCL. OpenCL is a library for interacting directly with the GPU on various different graphics cards. JOCL is a Java binding library for the OpenCL API.
Fair warning, this may be much more than you want to tackle, as you will be working at a much lower level than Swing.

I am not sure but it looks like you are using a BufferedImage of type BufferedImage.TYPE_INT_ARGB. This means that the BufferedImage is using a WritableRaster that is using a DataBuffer of type DataBufferInt. In its simplest form a DataBufferInt is nothing more than a wrapper around an int[]. If you can get a hold of the BufferedImage that the Canvas is using then get its WritableRaster and from there get the DataBufferInt:
WritableRaster raster = Canvas.image.getRaster();
DataBufferInt dataBuffer = (DataBufferInt)raster.getDataBuffer();
int[] pixels = dataBuffer.getData();
Now that you have the int[] that represents the pixels you can just loop over it and change the components:
for (int i = 0, len = pixels.len; i < len; ++i) {
int pixel = pixels[i];
int red = ((pixel & 0x00FF0000) >> 16) + amount;
if (red < 0) red = 0 else if (red > 255) red = 255;
int green = ((pixel & 0x0000FF00) >> 8) + amount;
if (green < 0) green = 0 else if (green > 255) green = 255;
int blue = (pixel & 0x000000FF) + amount;
if (blue < 0) blue = 0 else if (blue > 255) blue = 255;
pixels[i] = (pixels[i] & 0xFF000000) + (red << 16) + (green << 8) + blue;
}
This means that the pixels in the BufferedImage that the Preview has are being changed in-place without having to create another int[] of new pixels and another BufferedImage.
I am not sure if this will work but many times it helps in Java to cut out the middle-man and don't create as many objects.
If this does not work then look into Java Advanced Imaging.

How to get pixel value of Black and White Image?

I making App in netbeans platform using java Swing and JAI. In this i want to do image processing. I capture .tiff black and white image using X-Ray gun. after that i want to plot histogram of that Black and White image. so, for plot to histogram , first we have to get gray or black and white image pixel value. then we can plot histogram using this pixel value.so, how can i get this pixel value of black and white image?

This should work if you use java.awt.image.BufferedImage.
Since you want to create a histogram, I suppose you will loop through all the pixels. There is the method for returning a single pixel value.
int getRGB(int x, int y)
However, since looping will take place I suppose you'd want to use this one:
int[] getRGB(int startX, int startY, int w, int h, int[] rgbArray, int offset, int scansize)
When you get the array, use:
int alpha = (pixels[i] >> 24) & 0x000000FF;
int red = (pixels[i] >> 16) & 0x000000FF;
int green = (pixels[i] >>8 ) & 0x000000FF;
int blue = pixels[i] & 0x000000FF;
To extract the channel data. Not sure if the variables can be declared as byte (we are using only one byte of the integer in the array, although byte is signed and different arithmetic takes place - two's complement form), but you can declare them as short.
Then preform some maths on these values, for example:
int average = (red + green + blue) / 3;
This will return the average for the pixel, giving you a point you can use in a simple luminosity histogram.
EDIT:
Regarding histogram creation, I have used this class. It takes the image you want the histogram of as an argument to its setImage(BufferedImage image) method. Use updateHistogram() for array populating. The drawing data is in paintComponent(Graphics g). I must admit, it is sloppy, especially when calculating the offsets, but it can be easily simplified.
Here is the whole class:
class HistogramCtrl extends JComponent
{
BufferedImage m_image;
int[] m_histogramArray = new int[256]; //What drives our histogram
int m_maximumPixels;
public HistogramCtrl(){
m_maximumPixels = 0;
for(short i = 0; i<256; i++){
m_histogramArray[i] = 0;
}
}
void setImage(BufferedImage image){
m_image = image;
updateHistogram();
repaint();
}
void updateHistogram(){
if(m_image == null) return;
int[] pixels = m_image.getRGB(0, 0, m_image.getWidth(), m_image.getHeight(), null, 0, m_image.getWidth());
short currentValue = 0;
int red,green,blue;
for(int i = 0; i<pixels.length; i++){
red = (pixels[i] >> 16) & 0x000000FF;
green = (pixels[i] >>8 ) & 0x000000FF;
blue = pixels[i] & 0x000000FF;
currentValue = (short)((red + green + blue) / 3); //Current value gives the average //Disregard the alpha
assert(currentValue >= 0 && currentValue <= 255); //Something is awfully wrong if this goes off...
m_histogramArray[currentValue] += 1; //Increment the specific value of the array
}
m_maximumPixels = 0; //We need to have their number in order to scale the histogram properly
for(int i = 0; i < m_histogramArray.length;i++){ //Loop through the elements
if(m_histogramArray[i] > m_maximumPixels){ //And find the bigges value
m_maximumPixels = m_histogramArray[i];
}
}
}
protected void paintComponent(Graphics g){
assert(m_maximumPixels != 0);
Rectangle rect = g.getClipBounds();
Color oldColor = g.getColor();
g.setColor(new Color(210,210,210));
g.fillRect((int)rect.getX(), (int)rect.getY(), (int)rect.getWidth(), (int)rect.getHeight());
g.setColor(oldColor);
String zero = "0";
String thff = "255";
final short ctrlWidth = (short)rect.getWidth();
final short ctrlHeight = (short)rect.getHeight();
final short activeWidth = 256;
final short activeHeight = 200;
final short widthSpacing = (short)((ctrlWidth - activeWidth)/2);
final short heightSpacing = (short)((ctrlHeight - activeHeight)/2);
Point startingPoint = new Point();
final int substraction = -1;
startingPoint.x = widthSpacing-substraction;
startingPoint.y = heightSpacing+activeHeight-substraction;
g.drawString(zero,widthSpacing-substraction - 2,heightSpacing+activeHeight-substraction + 15);
g.drawString(thff,widthSpacing+activeWidth-substraction-12,heightSpacing+activeHeight-substraction + 15);
g.drawLine(startingPoint.x, startingPoint.y, widthSpacing+activeWidth-substraction, heightSpacing+activeHeight-substraction);
g.drawLine(startingPoint.x,startingPoint.y,startingPoint.x,heightSpacing-substraction);
double factorHeight = (double)activeHeight / m_maximumPixels; //The height divided by the number of pixels is the factor of multiplication for the other dots
Point usingPoint = new Point(startingPoint.x,startingPoint.y);
usingPoint.x+=2; //I want to move this two points in order to be able to draw the pixels with value 0 a bit away from the limit
Point tempPoint = new Point();
for(short i = 0; i<256; i++){
tempPoint.x = usingPoint.x;
tempPoint.y = (int)((heightSpacing+activeHeight-substraction) - (m_histogramArray[i] * factorHeight));
if((i!=0 && (i % 20 == 0)) || i == 255){
oldColor = g.getColor();
g.setColor(oldColor.brighter());
//Draw horizontal ruler sections
tempPoint.x = widthSpacing + i;
tempPoint.y = heightSpacing+activeHeight-substraction+4;
g.drawLine(tempPoint.x,tempPoint.y,widthSpacing + i,heightSpacing+activeHeight-substraction-4);
if(i <= 200){
//Draw vertical ruler sections
tempPoint.x = widthSpacing - substraction - 3;
tempPoint.y = heightSpacing+activeHeight-substraction-i;
g.drawLine(tempPoint.x,tempPoint.y,widthSpacing - substraction + 4, heightSpacing+activeHeight-substraction-i);
}
tempPoint.x = usingPoint.x;
tempPoint.y = usingPoint.y;
g.setColor(oldColor);
}
g.drawLine(usingPoint.x, usingPoint.y, tempPoint.x, tempPoint.y);
usingPoint.x++; //Set this to the next point
}
}
}