Count red pixel in a given image - java

I am new to Java and want to count red pixels in a given image. I have below code so far but not sure of what condition to add to check if pixel is red. I have below code so far. Thanks in advance.
public static int countRedPixels(Picture v){
BufferedImage image = (v.getBufferedImage());
int width = image.getWidth();
int height = image.getHeight();
int redCount = 0;
int pixelCount = 0;
for (int x = 0; x < width; x++) {
for (int y = 0; y < height ; y++) {
int rgb = image.getRGB(x, y);
//get rgbs
//int alpha = (rgb >>> 24) & 0xFF;
int red = (rgb >>> 16) & 0xFF;
int green = (rgb >>> 8) & 0xFF;
int blue = (rgb >>> 0) & 0xFF;
if (red == 255 && green == 0 && blue == 0 || image.getRGB(x, y) == 0xFFFF0000) {
redCount++;
}
pixelCount++;
}
}
System.out.println("Red Pixel Count:" + redCount);
System.out.println("Pixel Count:" + pixelCount);
return redCount;
}

Not sure if I'm missing something or you're really not seeing the forest for the trees. Anyway, comment turned answer:
Given that red means (255, 0, 0), you could do:
if (image.getRGB(x, y) == 0xFFFF0000) {
++redCount;
}
Or alternatively, if you don't care about alpha:
if (red == 255 && green == 0 && blue == 0) {
++redCount;
}

Related

Why do I have to save my BufferedImage before comparison?

I'm trying to analyze an image-based 3digit number captcha from an online resource. The numbers do not move at all. I use BufferedImage's getSubimage(...) method to extract each number from the captcha. I have saved (0-9) for each of the ones, tens and hundreds place. (So 30 numbers in total)
I read the bytes of the online image into a byte[] and then create a BufferedImage object like this:
BufferedImage captcha = ImageIO.read(new ByteArrayInputStream(captchaBytes));
Then I compare this image to a list of images on my drive:
BufferedImage[] nums = new BufferedImage[10];
//Load images into the array here... The code is removed.
for(int i = 0; i < nums.length; i++) {
double x;
System.out.println(x = bufferedImagesEqualConfidence(nums[i], firstNumberImage));
if(x > 0.98) {
System.out.println("equal to image " + i + ".jpeg");
isNewEntry = false;
break;
}
}
This is how I compare two images:
static double bufferedImagesEqualConfidence(BufferedImage img1, BufferedImage img2) {
double difference = 0;
int pixels = img1.getWidth() * img1.getHeight();
if (img1.getWidth() == img2.getWidth() && img1.getHeight() == img2.getHeight()) {
for (int x = 0; x < img1.getWidth(); x++) {
for (int y = 0; y < img1.getHeight(); y++) {
int rgbA = img1.getRGB(x, y);
int rgbB = img2.getRGB(x, y);
int redA = (rgbA >> 16) & 0xff;
int greenA = (rgbA >> 8) & 0xff;
int blueA = (rgbA) & 0xff;
int redB = (rgbB >> 16) & 0xff;
int greenB = (rgbB >> 8) & 0xff;
int blueB = (rgbB) & 0xff;
difference += Math.abs(redA - redB);
difference += Math.abs(greenA - greenB);
difference += Math.abs(blueA - blueB);
}
}
} else {
return 0.0;
}
return 1-((difference/(double)pixels) / 255.0);
}
The image is loaded completely from a HttpURLConnection object wrapped in my own HttpGet object. And so I do: byte[] captchaBytes = hg.readAndGetBytes(); Which I know works because when I save BufferedImage captcha = ImageIO.read(new ByteArrayInputStream(captchaBytes));, it saves as a valid image on my drive.
However, even though 2 images are actually the same, the result shows they are not similar at all. BUT, when I save the image I downloaded from the online resource first, re-read it, and compare, it shows they are equal. This is what I'm doing when I say I save it and re-read it:
File temp = new File("temp.jpeg");
ImageIO.write(secondNumberImage, "jpeg", temp);
secondNumberImage = ImageIO.read(temp);
Image format: JPEG
I know this may have something to do with compression from ImageIO.write(...), but how can I make it so that I don't have to save the image?
The problem was within my bufferedImagesEqualConfidence method. Simply comparing RGB was not enough. I had to compare individual R/G/B values.
My initial bufferedImagesEqualConfidence that didn't work was:
static double bufferedImagesEqualConfidence(BufferedImage img1, BufferedImage img2) {
int similarity = 0;
int pixels = img1.getWidth() * img1.getHeight();
if (img1.getWidth() == img2.getWidth() && img1.getHeight() == img2.getHeight()) {
for (int x = 0; x < img1.getWidth(); x++) {
for (int y = 0; y < img1.getHeight(); y++) {
if (img1.getRGB(x, y) == img2.getRGB(x, y)) {
similarity++;
}
}
}
} else {
return 0.0;
}
return similarity / (double)pixels;
}
(Source: Java Compare one BufferedImage to Another)
The bufferedImagesEqualConfidence that worked is:
static double bufferedImagesEqualConfidence(BufferedImage img1, BufferedImage img2) {
double difference = 0;
int pixels = img1.getWidth() * img1.getHeight();
if (img1.getWidth() == img2.getWidth() && img1.getHeight() == img2.getHeight()) {
for (int x = 0; x < img1.getWidth(); x++) {
for (int y = 0; y < img1.getHeight(); y++) {
int rgbA = img1.getRGB(x, y);
int rgbB = img2.getRGB(x, y);
int redA = (rgbA >> 16) & 0xff;
int greenA = (rgbA >> 8) & 0xff;
int blueA = (rgbA) & 0xff;
int redB = (rgbB >> 16) & 0xff;
int greenB = (rgbB >> 8) & 0xff;
int blueB = (rgbB) & 0xff;
difference += Math.abs(redA - redB);
difference += Math.abs(greenA - greenB);
difference += Math.abs(blueA - blueB);
}
}
} else {
return 0.0;
}
return 1-((difference/(double)pixels) / 255.0);
}
(Source: Image Processing in Java)
I guess to find similarity between two images you have to compare the individual R/G/B values for each pixel rather than just the whole RGB value.

Sobel Operator MaskX

Why my image quality after masking x get worse?
public void doMaskX() {
int[][] maskX = { { -1, -2, -1 }, { 0, 0, 0 }, { 1, 2, 1 } };
int rgb, alpha = 0;
int[][] square = new int[3][3];
for (int y = 0; y < width - 3; y++) {
for (int x = 0; x < height - 3; x++) {
int sum = 0;
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 3; j++) {
rgb = imgx.getRGB(y + i, x + j);
alpha = (rgb >> 24) & 0xff;
int red = (rgb >> 16) & 0xff;
int green = (rgb >> 8) & 0xff;
int blue = rgb & 0xff;
square[i][j] = (red + green + blue)/3;
sum += square[i][j] * maskX[i][j];
}
}
rgb = (alpha << 24) | (sum << 16) | (sum << 8) | sum;
imgx.setRGB(y, x, rgb);
}
}
writeImg();
}
the quality should be better of second image and why is yellow color appears?
It is important to realize that you are computing the intensity of the gradient here and that is what you are displaying. Therefore the intensity (or magnitude) is a positive number. You have to take the absolute value:
sum=Math.abs(sum);
If you take the y derivative also then you can combine:
sum=Math.sqrt(sumx*sumx+sumy*sumy);

Toggle between RGB channels

I need to toggle on/off RGB channels of an image, but I am stuck and my code is buggy.
Can you help me figure out how to do this the right way? This is my code:
The function channels is called when 1 of 3 checkboxes has changed its state and provides the arguments which are true == selected
public void channels(boolean red, boolean green, boolean blue) {
if (this.img != null) {// checks if the image is set
char r = 0xFF, g = 0xFF, b = 0xFF;
if (red == false) {
r = 0x00;
}
if (green == false) {
g = 0x00;
}
if (blue == false) {
b = 0x00;
}
BufferedImage tmp = new BufferedImage(
img.getWidth(),
img.getHeight(),
BufferedImage.TYPE_INT_RGB);
for (int i = 0; i < img.getWidth(); i++) {
for (int j = 0; j < img.getHeight(); j++) {
int rgb = img.getRGB(i, j);
int red = (rgb >> 16) & r;
int green = (rgb >> 8) & g;
int blue = (rgb >> 0) & b;
int gbr = (red << 16) | (green << 8) | blue;// EDITED
tmp.setRGB(i, j, gbr);
}
}
img = tmp;
repaint();
} else {
//show error
}
}
Thank you for your help!
How about this optimized version, with a lot less bit shifting?
public void channels(boolean showRed, boolean showGreen, boolean showBlue) {
if (this.origImg!= null) {// checks if the image is set
int channelMask = 0xff << 24 | (showRed ? 0xff : 0) << 16 | (showGreen ? 0xff : 0) << 8 | (showBlue ? 0xff : 0);
BufferedImage tmp = new BufferedImage(origImg.getWidth(), origImg.getHeight(), BufferedImage.TYPE_INT_RGB);
for (int i = 0; i < origImg.getWidth(); i++) {
for (int j = 0; j < origImg.getHeight(); j++) {
int rgb = origImg.getRGB(i, j);
tmp.setRGB(i, j, rgb & channelMask);
}
}
img = tmp;
repaint();
} else {
//show error
}
}
A faster approach yet, would probably be to use a channeled Raster, or at least a Raster configuration that allows band sub-sampling (see Raster.createChild(...) method, especially the last parameter).
LookupOp, as mentioned by #trashgod is also a good idea, and probably faster than the getRGB()/setRGB() approach.
It looks like you're shifting in the bits wrong. Shouldn't it be: int gbr = (red << 16) | (green << 8) | blue;? You basically want to shift back in the same order as how you shifted out to begin with.
Also, once you have cleared the corresponding colour, there's no way for you to get it back. You'll need to store a copy of the original image somewhere. When it's time to turn the channel back on, simply copy the original pixel from the original image back.
Assuming that you have the original image stored somewhere as origImg, I would modify your for loop so that if the channel is toggled on, copy from the original image.
for (int i = 0; i < img.getWidth(); i++) {
for (int j = 0; j < img.getHeight(); j++) {
int rgb = img.getRGB(i, j);
int origRGB = origImg.getRGB(i, j);
int redPixel = red ? (origRGB >> 16) & r : (rgb >> 16) & r;
int greenPixel = green ? (origRGB >> 8) & g : (rgb >> 8) & g;
int bluePixel = blue ? origRGB & b : rgb & b;
int gbr = (redPixel << 16) | (greenPixel << 8) | bluePixel;
tmp.setRGB(i, j, gbr);
}
}

Java BufferedImage Not Registering Transparent Pixels?

I have used the method ImageIO.read(File file); to read a PNG image file. However, when I use the getRGB(int x, int y) method on it to extract the alpha it always returns 255 whether the pixel is transparent or not. How do I remedy this inconvenience?
When converting packed int colors to Color objects, you need to tell it if it should calculate the alpha value or not.
new Color(image.getRGB(x, y), true).getAlpha();
See Color(int, boolean) for more details
Just wanted to point out that using the method getRGB(x,y) is extremely inefficient. If you want to get the pixels of an image you could extract the colours from each individual pixel and then store the pixel in an int array. Credit also to mota for explaining why this is inefficient see his post . Example below:
/**===============================================================================================
* Method that extracts pixel data from an image
* #return a 2d array representing the pixels of the image
=================================================================================================*/
public static int[][] getImageData(BufferedImage img) {
int height = img.getHeight();
int width = img.getWidth();
final byte[] imgPixels = ((DataBufferByte) img.getRaster().getDataBuffer()).getData();
final boolean is_Alpha_Present = img.getAlphaRaster() != null;
int[][] imgArr = new int[height][width];
if (is_Alpha_Present) {
final int pixelLength = 4; //number of bytes used to represent a pixel if alpha value present
for (int pixel = 0, row = 0, col = 0; pixel < imgPixels.length; pixel = pixel + pixelLength) {
int argb = 0;
argb += (((int) imgPixels[pixel] & 0xff) << 24); //getting the alpha for the pixel
argb += ((int) imgPixels[pixel + 1] & 0xff); //getting the blue colour
argb += (((int) imgPixels[pixel + 2] & 0xff) << 8); //getting the green colour
argb += (((int) imgPixels[pixel + 3] & 0xff) << 16); //getting the red colour
imgArr[row][col] = argb;
col++;
if (col == width) {
col = 0;
row++;
}
}
}
else {
final int pixelLength = 3;
for (int pixel = 0, row = 0, col = 0; pixel < imgPixels.length; pixel = pixel + pixelLength) {
int argb = 0;
argb += Integer.MIN_VALUE;
argb += ((int) imgPixels[pixel] & 0xff); //getting the blue colour
argb += (((int) imgPixels[pixel+1] & 0xff) << 8); //getting the green colour
argb += (((int) imgPixels[pixel+2] & 0xff) << 16); //getting the red colour
imgArr[row][col] = argb;
col++;
if (col == width) {
col = 0;
row++;
}
}
}
return imgArr;
}

Reading in a JPEG image and calculate image coordinates

I want to read in a JPEG image with a uniform gray background with several colored balls on it of the same size. I want a program which can take this image and record the coordinates of each ball. What's the best way to do this?
I agree with James. I used the following program once to find red boxes in an image (before most of the red boxes were recolored by the community):
/**
* #author karnokd, 2008.11.07.
* #version $Revision 1.0$
*/
public class RedLocator {
public static class Rect {
int x;
int y;
int x2;
int y2;
}
static List<Rect> rects = new LinkedList<Rect>();
static boolean checkRect(int x, int y) {
for (Rect r : rects) {
if (x >= r.x && x <= r.x2 && y >= r.y && y <= r.y2) {
return true;
}
}
return false;
}
public static void main(String[] args) throws Exception {
BufferedImage image = ImageIO.read(new File("fallout3worldmapfull.png"));
for (int y = 0; y < image.getHeight(); y++) {
for (int x = 0; x < image.getWidth(); x++) {
int c = image.getRGB(x,y);
int red = (c & 0x00ff0000) >> 16;
int green = (c & 0x0000ff00) >> 8;
int blue = c & 0x000000ff;
// check red-ness
if (red > 180 && green < 30 && blue < 30) {
if (!checkRect(x, y)) {
int tmpx = x;
int tmpy = y;
while (red > 180 && green < 30 && blue < 30) {
c = image.getRGB(tmpx++,tmpy);
red = (c & 0x00ff0000) >> 16;
green = (c & 0x0000ff00) >> 8;
blue = c & 0x000000ff;
}
tmpx -= 2;
c = image.getRGB(tmpx,tmpy);
red = (c & 0x00ff0000) >> 16;
green = (c & 0x0000ff00) >> 8;
blue = c & 0x000000ff;
while (red > 180 && green < 30 && blue < 30) {
c = image.getRGB(tmpx,tmpy++);
red = (c & 0x00ff0000) >> 16;
green = (c & 0x0000ff00) >> 8;
blue = c & 0x000000ff;
}
Rect r = new Rect();
r.x = x;
r.y = y;
r.x2 = tmpx;
r.y2 = tmpy - 2;
rects.add(r);
}
}
}
}
}
}
Might give you some hints. The image originates from here.
You can use the ImageIO library to read in an image by using one of the read() methods. This produces a BufferedImage which you can analyze for the separate colors. getRGB() is probably the best way to do this. You can compare this to the getRGB() of a Color object if you need to. That should be enough to get you started.

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