I would like to take a picture in true black and white in my app. I searched for solutions (in this site too), but I always found solution to put a photo in gray scale (for example in this topic), but it's not what I am looking for ...
I also found a topic proposing this :
public static Bitmap createContrast(Bitmap src, double value) {
// image size
int width = src.getWidth();
int height = src.getHeight();
// create output bitmap
Bitmap bmOut = Bitmap.createBitmap(width, height, src.getConfig());
// color information
int A, R, G, B;
int pixel;
// get contrast value
double contrast = Math.pow((100 + value) / 100, 2);
// scan through all pixels
for (int x = 0; x < width; ++x) {
for (int y = 0; y < height; ++y) {
// get pixel color
pixel = src.getPixel(x, y);
A = Color.alpha(pixel);
// apply filter contrast for every channel R, G, B
R = Color.red(pixel);
R = (int) (((((R / 255.0) - 0.5) * contrast) + 0.5) * 255.0);
if (R < 0) {
R = 0;
} else if (R > 255) {
R = 255;
}
G = Color.red(pixel);
G = (int) (((((G / 255.0) - 0.5) * contrast) + 0.5) * 255.0);
if (G < 0) {
G = 0;
} else if (G > 255) {
G = 255;
}
B = Color.red(pixel);
B = (int) (((((B / 255.0) - 0.5) * contrast) + 0.5) * 255.0);
if (B < 0) {
B = 0;
} else if (B > 255) {
B = 255;
}
// set new pixel color to output bitmap
bmOut.setPixel(x, y, Color.argb(A, R, G, B));
}
}
return bmOut;
}
But the image quality is horrible ...
Is anyone having an idea please?
Thank you
If you like the image to be 1bit black/white you can use a simple (& slow) threshold algorithm
public static Bitmap createBlackAndWhite(Bitmap src) {
int width = src.getWidth();
int height = src.getHeight();
// create output bitmap
Bitmap bmOut = Bitmap.createBitmap(width, height, src.getConfig());
// color information
int A, R, G, B;
int pixel;
// scan through all pixels
for (int x = 0; x < width; ++x) {
for (int y = 0; y < height; ++y) {
// get pixel color
pixel = src.getPixel(x, y);
A = Color.alpha(pixel);
R = Color.red(pixel);
G = Color.green(pixel);
B = Color.blue(pixel);
int gray = (int) (0.2989 * R + 0.5870 * G + 0.1140 * B);
// use 128 as threshold, above -> white, below -> black
if (gray > 128)
gray = 255;
else
gray = 0;
// set new pixel color to output bitmap
bmOut.setPixel(x, y, Color.argb(A, gray, gray, gray));
}
}
return bmOut;
}
But depending on what that will not look good, for better results you need a dithering algorithm, see Algorithm overview - this one is the threshold method.
For 256 levels of gray conversion:
according to http://www.mathworks.de/help/toolbox/images/ref/rgb2gray.html you calculate the gray value of each pixel as gray = 0.2989 * R + 0.5870 * G + 0.1140 * B
which would translate to
public static Bitmap createGrayscale(Bitmap src) {
int width = src.getWidth();
int height = src.getHeight();
// create output bitmap
Bitmap bmOut = Bitmap.createBitmap(width, height, src.getConfig());
// color information
int A, R, G, B;
int pixel;
// scan through all pixels
for (int x = 0; x < width; ++x) {
for (int y = 0; y < height; ++y) {
// get pixel color
pixel = src.getPixel(x, y);
A = Color.alpha(pixel);
R = Color.red(pixel);
G = Color.green(pixel);
B = Color.blue(pixel);
int gray = (int) (0.2989 * R + 0.5870 * G + 0.1140 * B);
// set new pixel color to output bitmap
bmOut.setPixel(x, y, Color.argb(A, gray, gray, gray));
}
}
return bmOut;
}
But that is pretty slow since you have to do that for millions of pixels separately.
https://stackoverflow.com/a/9377943/995891 has a much nicer way of achieving the same.
// code from that answer put into method from above
public static Bitmap createGrayscale(Bitmap src) {
int width = src.getWidth();
int height = src.getHeight();
Bitmap bmOut = Bitmap.createBitmap(width, height, Bitmap.Config.ARGB_8888);
Canvas canvas = new Canvas(bmOut);
ColorMatrix ma = new ColorMatrix();
ma.setSaturation(0);
Paint paint = new Paint();
paint.setColorFilter(new ColorMatrixColorFilter(ma));
canvas.drawBitmap(src, 0, 0, paint);
return bmOut;
}
G = Color.red(pixel);
G = Color.green(pixel);
B = Color.red(pixel);
B = Color.blue(pixel);
See if this changes (in bold) helps.
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