Keeping only the red/green/blue part of the image - image

I have made a very basic algorithm which extracts only the red / green / blue pixels of the image and displays them. However, it works well on some images and produces unexpected results in some. Like when I want to keep only green , it also keeps turquoise.
Turquoise is a shade of green but it is not what I want to display. I only want things that are 'visually' green.
Here is a sample output that shows what has gone wrong:
The algorithm picked up the turquoiose color of the flower pot on which the dog sits. The original image is here.
My algorithm is below (for the green one.) All the algorithms are akin to each other.
void keepGreen() {
for (int i = 0; // iterate over the pixels of the image
i < img.pixels.length;
i++) {
float inputRed = red(img.pixels[i]); // extract red
float inputGreen = green(img.pixels[i]); // extract green
float inputBlue = blue(img.pixels[i]); // extract blue
int pixel = -1;
float outputRed = -1;
float outputGreen = -1;
float outputBlue = -1;
if(inputRed <= inputGreen*0.9 && inputBlue <= inputGreen*0.9){ // check if the pixel is visually green
outputRed = inputRed; // yes, let it stay
outputGreen = inputGreen;
outputBlue = inputBlue;
}else{ // no, make it gray
int mostProminent =(int) max(inputRed, inputGreen, inputBlue);
int leastProminent =(int) min(inputRed, inputGreen, inputBlue);
int avg = (int) ((mostProminent + leastProminent) / 2);
outputRed = avg;
outputGreen = avg;
outputBlue = avg;
pixel = color(avg, avg, avg);
}
img.pixels[i] = color(outputRed, outputGreen, outputBlue); // set the pixel to the new value
}
img.updatePixels(); // update the image
image(img, WIDTH/2, HEIGHT/2, calculatedWidth, calculatedHeight); // display
}
How can I avoid those errors ?

Experiment with raising the red and blue thresholds individually, i.e inputGreen * 0.8 instead of inputGreen * 0.9 Use a tool like Instant Eyedropper or Pixel Picker to verify the RGB values in those colors that you don't want, and use that as feedback to set the thresholds for elimination of the colors that you don't want.
You might also want to consider the luminance level in your calculations. The pixels being picked up on the flower pot are darker than the other pixels on the flower pot.

Just because Blue is less than Green doesn't mean the pixel doesn't look green. For example, turquoise might be red=50, blue=200, green=150. Perhaps you need to (also) gray out pixels that have substantial green in their own right, regardless of red/blue.

Related

Processing: Efficiently create uniform grid

I'm trying to create a grid of an image (in the way one would tile a background with). Here's what I've been using:
PImage bgtile;
PGraphics bg;
int tilesize = 50;
void setup() {
int t = millis();
fullScreen(P2D);
background(0);
bgtile = loadImage("bgtile.png");
int bgw = ceil( ((float) width) / tilesize) + 1;
int bgh = ceil( ((float) height) / tilesize) + 1;
bg = createGraphics(bgw*tilesize,bgh*tilesize);
bg.beginDraw();
for(int i = 0; i < bgw; i++){
for(int j = 0; j < bgh; j++){
bg.image(bgtile, i*tilesize, j*tilesize, tilesize, tilesize);
}
}
bg.endDraw();
print(millis() - t);
}
The timing code says that this takes about a quarter of a second, but by my count there's a full second once the window opens before anything shows up on screen (which should happen as soon as draw is first run). Is there a faster way to get this same effect? (I want to avoid rendering bgtile hundreds of times in the draw loop for obvious reasons)
One way could be to make use of the GPU and let OpenGL repeat a texture for you.
Processing makes it fairly easy to repeat a texture via textureWrap(REPEAT)
Instead of drawing an image you'd make your own quad shape and instead of calling vertex(x, y) for example, you'd call vertex(x, y, u, v); passing texture coordinates (more low level info on the OpenGL link above). The simple idea is x,y would control the geometry on screen and u,v would control how the texture is applied to the geometry.
Another thing you can control is textureMode() which allows you control how you specify the texture coordinates (U, V):
IMAGE mode is the default: you use pixel coordinates (based on the dimensions of the texture)
NORMAL mode uses values between 0.0 and 1.0 (also known as normalised values) where 1.0 means the maximum the texture can go (e.g. image width for U or image height for V) and you don't need to worry about knowing the texture image dimensions
Here's a basic example based on the textureMode() example above:
PImage img;
void setup() {
fullScreen(P2D);
noStroke();
img = loadImage("https://processing.org/examples/moonwalk.jpg");
// texture mode can be IMAGE (pixel dimensions) or NORMAL (0.0 to 1.0)
// normal means 1.0 is full width (for U) or height (for V) without having to know the image resolution
textureMode(NORMAL);
// this is what will make handle tiling for you
textureWrap(REPEAT);
}
void draw() {
// drag mouse on X axis to change tiling
int tileRepeats = (int)map(constrain(mouseX,0,width), 0, width, 1, 100);
// draw a textured quad
beginShape(QUAD);
// set the texture
texture(img);
// x , y , U , V
vertex(0 , 0 , 0 , 0);
vertex(width, 0 , tileRepeats, 0);
vertex(width, height, tileRepeats, tileRepeats);
vertex(0 , height, 0 , tileRepeats);
endShape();
text((int)frameRate+"fps",15,15);
}
Drag the mouse on the Y axis to control the number of repetitions.
In this simple example both vertex coordinates and texture coordinates are going clockwise (top left, top right, bottom right, bottom left order).
There are probably other ways to achieve the same result: using a PShader comes to mind.
Your approach caching the tiles in setup is ok.
Even flattening your nested loop into a single loop at best may only shave a few milliseconds off, but nothing substantial.
If you tried to cache my snippet above it would make a minimal difference.
In this particular case, because of the back and forth between Java/OpenGL (via JOGL), as far as I can tell using VisualVM, it looks like there's not a lot of room for improvement since simply swapping buffers takes so long (e.g. bg.image()):
An easy way to do this would be to use processing's built in get(); which saves a PImage of the coordinates you pass, for example: PImage pic = get(0, 0, width, height); will capture a "screenshot" of your entire window. So, you can create the image like you already are, and then take a screenshot and display that screenshot.
PImage bgtile;
PGraphics bg;
PImage screenGrab;
int tilesize = 50;
void setup() {
fullScreen(P2D);
background(0);
bgtile = loadImage("bgtile.png");
int bgw = ceil(((float) width) / tilesize) + 1;
int bgh = ceil(((float) height) / tilesize) + 1;
bg = createGraphics(bgw * tilesize, bgh * tilesize);
bg.beginDraw();
for (int i = 0; i < bgw; i++) {
for (int j = 0; j < bgh; j++) {
bg.image(bgtile, i * tilesize, j * tilesize, tilesize, tilesize);
}
}
bg.endDraw();
screenGrab = get(0, 0, width, height);
}
void draw() {
image(screenGrab, 0, 0);
}
This will still take a little bit to generate the image, but once it does, there is no need to use the for loops again unless you change the tilesize.
#George Profenza's answer looks more efficient than my solution, but mine may take a little less modification to the code you already have.

Using Processing for image visualization: pixel color thresholds

Image to be manipulated, hoping to identify each white dot on each picture with a counter
PImage blk;
void setup() {
size(640, 480);
blk=loadImage("img.png");
}
void draw () {
loadPixels();
blk.loadPixels();
int i = 0;
for (int x = 0; x < width; x++) {
for (int y = 0; y < height; y++) {
int loc = x+y*width;
pixels [loc] = blk.pixels[loc];
if (blk.pixels[loc] == 0) {
if (blk.pixels [loc]+1 != 0) {
i++;
}
}
float r = red(blk.pixels[loc]);
float g = green(blk.pixels[loc]);
float b = blue(blk.pixels[loc]);
pixels [loc] = color(r, g, b);
}
}
System.out.println (i);
updatePixels();
}
The main problem is within my if statement, not sure to approach it logically.
I'm unsure where this is exactly going, but I can help you find the white pixels. Here, I just counted 7457 "white" pixels (then I turned them red so you can see where they are and adjust the threshold if you want to get more or less of them):
Of course, this is just a proof of concept which you should be able to adapt to your needs.
PImage blk;
void setup() {
size(640, 480);
blk=loadImage("img.png");
blk.loadPixels();
int whitePixelsCount = 0;
// I'm doing this in the 'setup()' method because I don't need to do it 60 times per second
// Once it's done once I can just use the image as modified unless you want several
// different versions (which you can calculate once anyway then store in different PImages)
for (int i = 0; i < blk.width * blk.height; i++) {
float r = red(blk.pixels[i]);
float g = green(blk.pixels[i]);
float b = blue(blk.pixels[i]);
// In RGB, the brightness of each color is represented by it's intensity
// So here I'm checking the "average intensity" of the color to see how bright it is
// And I compare it to 100 since 255 is the max and I wanted this simple, but you can
// play with this threshold as much as you like
if ((r+g+b)/3 > 100) {
whitePixelsCount++;
// Here I'm making those pixels red so you can see where they are.
// It's easier to adjust the threshold if you can see what you're doing
blk.pixels[i] = color(255, 0, 0);
}
}
println(whitePixelsCount);
updatePixels();
}
void draw () {
image(blk, 0, 0);
}
In short (you'll read this in the comments too), we count the pixels according to a threshold we can adjust. To make things more obvious for you, I colored the "white" pixels red. You can lower or raise the threshold according to what you see this way, and once you know what you want you can get rid of the color.
There is a difficulty here, which is that the image isn't "black and white", but more greyscale - which is totally normal, but makes things harder for what you seem to be trying to do. You'll probably have to tinker a lot to get to the exact ratio which interests you. It could help a lot if you edited the original image in GiMP or another image software which lets you adjust contrast and brightness. It's kinda cheating, but it it doesn't work right off the bat this strategy could save you some work.
Have fun!

How to disable Center Color in polygon with multicolored gradient?

I am trying to build a polygon using only two colors for all vertex. But the gdiplus library automatically inserts an white center color blending all the figure. I would like to disable the center color, instead workarounding it by using SetCenterColor() available in PathGradientBrush class. Shifting the default position using SetCenterPoint() to a far way position is very inelegant. Is that possible?
Thanks
A sample follows:
CMyGDIPlus gdi(this); // use your class instead
using namespace Gdiplus;
Graphics & graphics = gdi.GetGraphics();
graphics.SetSmoothingMode(SmoothingModeNone);
Gdiplus::Rect gRect;
graphics.GetVisibleClipBounds(&gRect);
int i;
int colorSize = 4;
GraphicsPath path;
Point arrPoint[4];
Color arrColors[4];
arrPoint[0].X = gRect.GetLeft();
arrPoint[0].Y = gRect.GetTop();
arrPoint[1].X = gRect.GetRight();
arrPoint[1].Y = gRect.GetTop()+100;
arrPoint[2].X = gRect.GetRight();
arrPoint[2].Y = gRect.GetBottom();
arrPoint[3].X = gRect.GetLeft();
arrPoint[3].Y = gRect.GetBottom()-100;
for(i = 0; i < colorSize; i++)
{
if(i < 2)
arrColors[i].SetFromCOLORREF(RGB(0, 128, 0)); // green
else
arrColors[i].SetFromCOLORREF(RGB(0, 0, 192)); // blue
}
path.AddLines(arrPoint, 4);
PathGradientBrush pathBrush(&path);
pathBrush.SetSurroundColors(arrColors, &colorSize);
pathBrush.SetGammaCorrection(TRUE);
graphics.FillPath(&pathBrush, &path);
You only need to calculate the color value of the center point.
To average the values (e.g. (r1 + r2) / 2). This works better for lightening/darkening colors and creating gradients.
Refer: Algorithm for Additive Color Mixing for RGB Values
Add : pathBrush.SetCenterColor(Color(0, 128*0.5, 192*0.5));
Debug:

Retrieve color information from images

I need to determine the amount/quality of color in an image in order to compare it with other images and recommend a user (owner of the image) maybe he needs to print it in black and white and not in color.
So far I'm analyzing the image and extracting some data of it:
The number of different colors I find in the image
The percentage of color in the whole page (color pixels / total pixels)
For further analysis I may need other characteristic of these images. Do you know what else is important (or I'm missing here) in image analysis?
After some time I found a missing characteristic (very important) which helped me a lot with the analysis of the images. I don't know if there is a name for that but I called it the average color of the image:
When I was looping over all the pixels of the image and counting each color I also retrieved the information of the RGB values and summarized all the Reds, Greens and Blues of all the pixels. Just to come up with this average color which, again, saved my life when I wanted to compare some kind of images.
The code is something like this:
File f = new File("image.jpg");
BufferedImage im = ImageIO.read(f);
int tot = 0;
int red = 0;
int blue= 0;
int green = 0;
int w = im.getWidth();
int h = im.getHeight();
// Going over all the pixels
for (int i=0;i<w;i++){
for (int j=0;j<h;j++){
int pix = im.getRGB(i, j); //
if (!sameARGB(pix)) { // Compares the RGB values
tot+=1;
red+=pix.getRed();
green+=pix.getGreen();
blue+=pix.getBlue();
}
}
}
And you should get the results like this:
// Percentage of color on the image
double per = (double)tot/(h*w);
// Average color <-------------
Color c = new Color((double)red/tot,(double)green/tot,(double)blue/tot);

Determine font color based on background color

Given a system (a website for instance) that lets a user customize the background color for some section but not the font color (to keep number of options to a minimum), is there a way to programmatically determine if a "light" or "dark" font color is necessary?
I'm sure there is some algorithm, but I don't know enough about colors, luminosity, etc to figure it out on my own.
I encountered similar problem. I had to find a good method of selecting contrastive font color to display text labels on colorscales/heatmaps. It had to be universal method and generated color had to be "good looking", which means that simple generating complementary color was not good solution - sometimes it generated strange, very intensive colors that were hard to watch and read.
After long hours of testing and trying to solve this problem, I found out that the best solution is to select white font for "dark" colors, and black font for "bright" colors.
Here's an example of function I am using in C#:
Color ContrastColor(Color color)
{
int d = 0;
// Counting the perceptive luminance - human eye favors green color...
double luminance = (0.299 * color.R + 0.587 * color.G + 0.114 * color.B)/255;
if (luminance > 0.5)
d = 0; // bright colors - black font
else
d = 255; // dark colors - white font
return Color.FromArgb(d, d, d);
}
This was tested for many various colorscales (rainbow, grayscale, heat, ice, and many others) and is the only "universal" method I found out.
Edit
Changed the formula of counting a to "perceptive luminance" - it really looks better! Already implemented it in my software, looks great.
Edit 2
#WebSeed provided a great working example of this algorithm: http://codepen.io/WebSeed/full/pvgqEq/
Based on Gacek's answer but directly returning color constants (additional modifications see below):
public Color ContrastColor(Color iColor)
{
// Calculate the perceptive luminance (aka luma) - human eye favors green color...
double luma = ((0.299 * iColor.R) + (0.587 * iColor.G) + (0.114 * iColor.B)) / 255;
// Return black for bright colors, white for dark colors
return luma > 0.5 ? Color.Black : Color.White;
}
Note: I removed the inversion of the luma value to make bright colors have a higher value, what seems more natural to me and is also the 'default' calculation method.
(Edit: This has since been adopted in the original answer, too)
I used the same constants as Gacek from here since they worked great for me.
You can also implement this as an Extension Method using the following signature:
public static Color ContrastColor(this Color iColor)
You can then easily call it via
foregroundColor = backgroundColor.ContrastColor().
Thank you #Gacek. Here's a version for Android:
#ColorInt
public static int getContrastColor(#ColorInt int color) {
// Counting the perceptive luminance - human eye favors green color...
double a = 1 - (0.299 * Color.red(color) + 0.587 * Color.green(color) + 0.114 * Color.blue(color)) / 255;
int d;
if (a < 0.5) {
d = 0; // bright colors - black font
} else {
d = 255; // dark colors - white font
}
return Color.rgb(d, d, d);
}
And an improved (shorter) version:
#ColorInt
public static int getContrastColor(#ColorInt int color) {
// Counting the perceptive luminance - human eye favors green color...
double a = 1 - (0.299 * Color.red(color) + 0.587 * Color.green(color) + 0.114 * Color.blue(color)) / 255;
return a < 0.5 ? Color.BLACK : Color.WHITE;
}
My Swift implementation of Gacek's answer:
func contrastColor(color: UIColor) -> UIColor {
var d = CGFloat(0)
var r = CGFloat(0)
var g = CGFloat(0)
var b = CGFloat(0)
var a = CGFloat(0)
color.getRed(&r, green: &g, blue: &b, alpha: &a)
// Counting the perceptive luminance - human eye favors green color...
let luminance = 1 - ((0.299 * r) + (0.587 * g) + (0.114 * b))
if luminance < 0.5 {
d = CGFloat(0) // bright colors - black font
} else {
d = CGFloat(1) // dark colors - white font
}
return UIColor( red: d, green: d, blue: d, alpha: a)
}
Javascript [ES2015]
const hexToLuma = (colour) => {
const hex = colour.replace(/#/, '');
const r = parseInt(hex.substr(0, 2), 16);
const g = parseInt(hex.substr(2, 2), 16);
const b = parseInt(hex.substr(4, 2), 16);
return [
0.299 * r,
0.587 * g,
0.114 * b
].reduce((a, b) => a + b) / 255;
};
Ugly Python if you don't feel like writing it :)
'''
Input a string without hash sign of RGB hex digits to compute
complementary contrasting color such as for fonts
'''
def contrasting_text_color(hex_str):
(r, g, b) = (hex_str[:2], hex_str[2:4], hex_str[4:])
return '000' if 1 - (int(r, 16) * 0.299 + int(g, 16) * 0.587 + int(b, 16) * 0.114) / 255 < 0.5 else 'fff'
Thanks for this post.
For whoever might be interested, here's an example of that function in Delphi:
function GetContrastColor(ABGColor: TColor): TColor;
var
ADouble: Double;
R, G, B: Byte;
begin
if ABGColor <= 0 then
begin
Result := clWhite;
Exit; // *** EXIT RIGHT HERE ***
end;
if ABGColor = clWhite then
begin
Result := clBlack;
Exit; // *** EXIT RIGHT HERE ***
end;
// Get RGB from Color
R := GetRValue(ABGColor);
G := GetGValue(ABGColor);
B := GetBValue(ABGColor);
// Counting the perceptive luminance - human eye favors green color...
ADouble := 1 - (0.299 * R + 0.587 * G + 0.114 * B) / 255;
if (ADouble < 0.5) then
Result := clBlack // bright colors - black font
else
Result := clWhite; // dark colors - white font
end;
This is such a helpful answer. Thanks for it!
I'd like to share an SCSS version:
#function is-color-light( $color ) {
// Get the components of the specified color
$red: red( $color );
$green: green( $color );
$blue: blue( $color );
// Compute the perceptive luminance, keeping
// in mind that the human eye favors green.
$l: 1 - ( 0.299 * $red + 0.587 * $green + 0.114 * $blue ) / 255;
#return ( $l < 0.5 );
}
Now figuring out how to use the algorithm to auto-create hover colors for menu links. Light headers get a darker hover, and vice-versa.
Short Answer:
Calculate the luminance (Y) of the given color, and flip the text either black or white based on a pre-determined middle contrast figure. For a typical sRGB display, flip to white when Y < 0.4 (i.e. 40%)
Longer Answer
Not surprisingly, nearly every answer here presents some misunderstanding, and/or is quoting incorrect coefficients. The only answer that is actually close is that of Seirios, though it relies on WCAG 2 contrast which is known to be incorrect itself.
If I say "not surprisingly", it is due in part to the massive amount of misinformation on the internet on this particular subject. The fact this field is still a subject of active research and unsettled science adds to the fun. I come to this conclusion as the result of the last few years of research into a new contrast prediction method for readability.
The field of visual perception is dense and abstract, as well as developing, so it is common for misunderstandings to exist. For instance, HSV and HSL are not even close to perceptually accurate. For that you need a perceptually uniform model such as CIELAB or CIELUV or CIECAM02 etc.
Some misunderstandings have even made their way into standards, such as the contrast part of WCAG 2 (1.4.3), which has been demonstrated as incorrect over much of its range.
First Fix:
The coefficients shown in many answers here are (.299, .587, .114) and are wrong, as they pertain to a long obsolete system known as NTSC YIQ, the analog broadcast system in North America some decades ago. While they may still be used in some YCC encoding specs for backwards compatibility, they should not be used in an sRGB context.
The coefficients for sRGB and Rec.709 (HDTV) are:
Red: 0.2126
Green: 0.7152
Blue: 0.0722
Other color spaces like Rec2020 or AdobeRGB use different coefficients, and it is important to use the correct coefficients for a given color space.
The coefficients can not be applied directly to 8 bit sRGB encoded image or color data. The encoded data must first be linearized, then the coefficients applied to find the luminance (light value) of the given pixel or color.
For sRGB there is a piecewise transform, but as we are only interested in the perceived lightness contrast to find the point to "flip" the text from black to white, we can take a shortcut via the simple gamma method.
Andy's Shortcut to Luminance & Lightness
Divide each sRGB color by 255.0, then raise to the power of 2.2, then multiply by the coefficients and sum them to find estimated luminance.
let Ys = Math.pow(sR/255.0,2.2) * 0.2126 +
Math.pow(sG/255.0,2.2) * 0.7152 +
Math.pow(sB/255.0,2.2) * 0.0722; // Andy's Easy Luminance for sRGB. For Rec709 HDTV change the 2.2 to 2.4
Here, Y is the relative luminance from an sRGB monitor, on a 0.0 to 1.0 scale. This is not relative to perception though, and we need further transforms to fit our human visual perception of the relative lightness, and also of the perceived contrast.
The 40% Flip
But before we get there, if you are only looking for a basic point to flip the text from black to white or vice versa, the cheat is to use the Y we just derived, and make the flip point about Y = 0.40;. so for colors higher than 0.4 Y, make the text black #000 and for colors darker than 0.4 Y, make the text white #fff.
let textColor = (Ys < 0.4) ? "#fff" : "#000"; // Low budget down and dirty text flipper.
Why 40% and not 50%? Our human perception of lightness/darkness and of contrast is not linear. For a self illuminated display, it so happens that 0.4 Y is about middle contrast under most typical conditions.
Yes it varies, and yes this is an over simplification. But if you are flipping text black or white, the simple answer is a useful one.
Perceptual Bonus Round
Predicting the perception of a given color and lightness is still a subject of active research, and not entirely settled science. The L* (Lstar) of CIELAB or LUV has been used to predict perceptual lightness, and even to predict perceived contrast. However, L* works well for surface colors in a very defined/controlled environment, and does not work as well for self illuminated displays.
While this varies depending on not only the display type and calibration, but also your environment and the overall page content, if you take the Y from above, and raise it by around ^0.685 to ^0.75, you'll find that 0.5 is typically the middle point to flip the text from white to black.
let textColor = (Math.pow(Ys,0.75) < 0.5) ? "#fff" : "#000"; // perceptually based text flipper.
Using the exponent 0.685 will make the text color swap on a darker color, and using 0.8 will make the text swap on a lighter color.
Spatial Frequency Double Bonus Round
It is useful to note that contrast is NOT just the distance between two colors. Spatial frequency, in other words font weight and size, are also CRITICAL factors that cannot be ignored.
That said, you may find that when colors are in the midrange, that you'd want to increase the size and or weight of the font.
let textSize = "16px";
let textWeight = "normal";
let Ls = Math.pow(Ys,0.7);
if (Ls > 0.33 && Ls < 0.66) {
textSize = "18px";
textWeight = "bold";
} // scale up fonts for the lower contrast mid luminances.
Hue R U
It's outside the scope of this post to delve deeply, but above we are ignoring hue and chroma. Hue and chroma do have an effect, such as Helmholtz Kohlrausch, and the simpler luminance calculations above do not always predict intensity due to saturated hues.
To predict these more subtle aspects of perception, a complete appearance model is needed. R. Hunt, M. Fairshild, E. Burns are a few authors worth looking into if you want to plummet down the rabbit hole of human visual perception...
For this narrow purpose, we could re-weight the coefficients slightly, knowing that green makes up the majority of of luminance, and pure blue and pure red should always be the darkest of two colors. What tends to happen using the standard coefficients, is middle colors with a lot of blue or red may flip to black at a lower than ideal luminance, and colors with a high green component may do the opposite.
That said, I find this is best addressed by increasing font size and weight in the middle colors.
Putting it all together
So we'll assume you'll send this function a hex string, and it will return a style string that can be sent to a particular HTML element.
Check out the CODEPEN, inspired by the one Seirios did:
CodePen: Fancy Font Flipping
One of the things the Codepen code does is increase the text size for the lower contrast midrange. Here's a sample:
And if you want to play around with some of these concepts, see the SAPC development site at https://www.myndex.com/SAPC/ clicking on "research mode" provides interactive experiments to demonstrate these concepts.
Terms of enlightenment
Luminance: Y (relative) or L (absolute cd/m2) a spectrally weighted but otherwise linear measure of light. Not to be confused with "Luminosity".
Luminosity: light over time, useful in astronomy.
Lightness: L* (Lstar) perceptual lightness as defined by the CIE. Some models have a related lightness J*.
I had the same problem but i had to develop it in PHP. I used #Garek's solution and i also used this answer:
Convert hex color to RGB values in PHP to convert HEX color code to RGB.
So i'm sharing it.
I wanted to use this function with given Background HEX color, but not always starting from '#'.
//So it can be used like this way:
$color = calculateColor('#804040');
echo $color;
//or even this way:
$color = calculateColor('D79C44');
echo '<br/>'.$color;
function calculateColor($bgColor){
//ensure that the color code will not have # in the beginning
$bgColor = str_replace('#','',$bgColor);
//now just add it
$hex = '#'.$bgColor;
list($r, $g, $b) = sscanf($hex, "#%02x%02x%02x");
$color = 1 - ( 0.299 * $r + 0.587 * $g + 0.114 * $b)/255;
if ($color < 0.5)
$color = '#000000'; // bright colors - black font
else
$color = '#ffffff'; // dark colors - white font
return $color;
}
Flutter implementation
Color contrastColor(Color color) {
if (color == Colors.transparent || color.alpha < 50) {
return Colors.black;
}
double luminance = (0.299 * color.red + 0.587 * color.green + 0.114 * color.blue) / 255;
return luminance > 0.5 ? Colors.black : Colors.white;
}
Based on Gacek's answer, and after analyzing #WebSeed's example with the WAVE browser extension, I've come up with the following version that chooses black or white text based on contrast ratio (as defined in W3C's Web Content Accessibility Guidelines (WCAG) 2.1), instead of luminance.
This is the code (in javascript):
// As defined in WCAG 2.1
var relativeLuminance = function (R8bit, G8bit, B8bit) {
var RsRGB = R8bit / 255.0;
var GsRGB = G8bit / 255.0;
var BsRGB = B8bit / 255.0;
var R = (RsRGB <= 0.03928) ? RsRGB / 12.92 : Math.pow((RsRGB + 0.055) / 1.055, 2.4);
var G = (GsRGB <= 0.03928) ? GsRGB / 12.92 : Math.pow((GsRGB + 0.055) / 1.055, 2.4);
var B = (BsRGB <= 0.03928) ? BsRGB / 12.92 : Math.pow((BsRGB + 0.055) / 1.055, 2.4);
return 0.2126 * R + 0.7152 * G + 0.0722 * B;
};
var blackContrast = function(r, g, b) {
var L = relativeLuminance(r, g, b);
return (L + 0.05) / 0.05;
};
var whiteContrast = function(r, g, b) {
var L = relativeLuminance(r, g, b);
return 1.05 / (L + 0.05);
};
// If both options satisfy AAA criterion (at least 7:1 contrast), use preference
// else, use higher contrast (white breaks tie)
var chooseFGcolor = function(r, g, b, prefer = 'white') {
var Cb = blackContrast(r, g, b);
var Cw = whiteContrast(r, g, b);
if(Cb >= 7.0 && Cw >= 7.0) return prefer;
else return (Cb > Cw) ? 'black' : 'white';
};
A working example may be found in my fork of #WebSeed's codepen, which produces zero low contrast errors in WAVE.
As Kotlin / Android extension:
fun Int.getContrastColor(): Int {
// Counting the perceptive luminance - human eye favors green color...
val a = 1 - (0.299 * Color.red(this) + 0.587 * Color.green(this) + 0.114 * Color.blue(this)) / 255
return if (a < 0.5) Color.BLACK else Color.WHITE
}
An implementation for objective-c
+ (UIColor*) getContrastColor:(UIColor*) color {
CGFloat red, green, blue, alpha;
[color getRed:&red green:&green blue:&blue alpha:&alpha];
double a = ( 0.299 * red + 0.587 * green + 0.114 * blue);
return (a > 0.5) ? [[UIColor alloc]initWithRed:0 green:0 blue:0 alpha:1] : [[UIColor alloc]initWithRed:255 green:255 blue:255 alpha:1];
}
iOS Swift 3.0 (UIColor extension):
func isLight() -> Bool
{
if let components = self.cgColor.components, let firstComponentValue = components[0], let secondComponentValue = components[1], let thirdComponentValue = components[2] {
let firstComponent = (firstComponentValue * 299)
let secondComponent = (secondComponentValue * 587)
let thirdComponent = (thirdComponentValue * 114)
let brightness = (firstComponent + secondComponent + thirdComponent) / 1000
if brightness < 0.5
{
return false
}else{
return true
}
}
print("Unable to grab components and determine brightness")
return nil
}
Swift 4 Example:
extension UIColor {
var isLight: Bool {
let components = cgColor.components
let firstComponent = ((components?[0]) ?? 0) * 299
let secondComponent = ((components?[1]) ?? 0) * 587
let thirdComponent = ((components?[2]) ?? 0) * 114
let brightness = (firstComponent + secondComponent + thirdComponent) / 1000
return !(brightness < 0.6)
}
}
UPDATE - Found that 0.6 was a better test bed for the query
Note there is an algorithm for this in the google closure library that references a w3c recommendation: http://www.w3.org/TR/AERT#color-contrast. However, in this API you provide a list of suggested colors as a starting point.
/**
* Find the "best" (highest-contrast) of the suggested colors for the prime
* color. Uses W3C formula for judging readability and visual accessibility:
* http://www.w3.org/TR/AERT#color-contrast
* #param {goog.color.Rgb} prime Color represented as a rgb array.
* #param {Array<goog.color.Rgb>} suggestions Array of colors,
* each representing a rgb array.
* #return {!goog.color.Rgb} Highest-contrast color represented by an array.
*/
goog.color.highContrast = function(prime, suggestions) {
var suggestionsWithDiff = [];
for (var i = 0; i < suggestions.length; i++) {
suggestionsWithDiff.push({
color: suggestions[i],
diff: goog.color.yiqBrightnessDiff_(suggestions[i], prime) +
goog.color.colorDiff_(suggestions[i], prime)
});
}
suggestionsWithDiff.sort(function(a, b) { return b.diff - a.diff; });
return suggestionsWithDiff[0].color;
};
/**
* Calculate brightness of a color according to YIQ formula (brightness is Y).
* More info on YIQ here: http://en.wikipedia.org/wiki/YIQ. Helper method for
* goog.color.highContrast()
* #param {goog.color.Rgb} rgb Color represented by a rgb array.
* #return {number} brightness (Y).
* #private
*/
goog.color.yiqBrightness_ = function(rgb) {
return Math.round((rgb[0] * 299 + rgb[1] * 587 + rgb[2] * 114) / 1000);
};
/**
* Calculate difference in brightness of two colors. Helper method for
* goog.color.highContrast()
* #param {goog.color.Rgb} rgb1 Color represented by a rgb array.
* #param {goog.color.Rgb} rgb2 Color represented by a rgb array.
* #return {number} Brightness difference.
* #private
*/
goog.color.yiqBrightnessDiff_ = function(rgb1, rgb2) {
return Math.abs(
goog.color.yiqBrightness_(rgb1) - goog.color.yiqBrightness_(rgb2));
};
/**
* Calculate color difference between two colors. Helper method for
* goog.color.highContrast()
* #param {goog.color.Rgb} rgb1 Color represented by a rgb array.
* #param {goog.color.Rgb} rgb2 Color represented by a rgb array.
* #return {number} Color difference.
* #private
*/
goog.color.colorDiff_ = function(rgb1, rgb2) {
return Math.abs(rgb1[0] - rgb2[0]) + Math.abs(rgb1[1] - rgb2[1]) +
Math.abs(rgb1[2] - rgb2[2]);
};
base R version of #Gacek's answer to get luminance (you can apply your own threshold easily)
# vectorized
luminance = function(col) c(c(.299, .587, .114) %*% col2rgb(col)/255)
Usage:
luminance(c('black', 'white', '#236FAB', 'darkred', '#01F11F'))
# [1] 0.0000000 1.0000000 0.3730039 0.1629843 0.5698039
If you're manipulating color spaces for visual effect it's generally easier to work in HSL (Hue, Saturation and Lightness) than RGB. Moving colours in RGB to give naturally pleasing effects tends to be quite conceptually difficult, whereas converting into HSL, manipulating there, then converting back out again is more intuitive in concept and invariably gives better looking results.
Wikipedia has a good introduction to HSL and the closely related HSV. And there's free code around the net to do the conversion (for example here is a javascript implementation)
What precise transformation you use is a matter of taste, but personally I'd have thought reversing the Hue and Lightness components would be certain to generate a good high contrast colour as a first approximation, but you can easily go for more subtle effects.
You can have any hue text on any hue background and ensure that it is legible. I do it all the time. There's a formula for this in Javascript on Readable Text in Colour – STW*
As it says on that link, the formula is a variation on the inverse-gamma adjustment calculation, though a bit more manageable IMHO.
The menus on the right-hand side of that link and its associated pages use randomly-generated colours for text and background, always legible. So yes, clearly it can be done, no problem.
An Android variation that captures the alpha as well.
(thanks #thomas-vos)
/**
* Returns a colour best suited to contrast with the input colour.
*
* #param colour
* #return
*/
#ColorInt
public static int contrastingColour(#ColorInt int colour) {
// XXX https://stackoverflow.com/questions/1855884/determine-font-color-based-on-background-color
// Counting the perceptive luminance - human eye favors green color...
double a = 1 - (0.299 * Color.red(colour) + 0.587 * Color.green(colour) + 0.114 * Color.blue(colour)) / 255;
int alpha = Color.alpha(colour);
int d = 0; // bright colours - black font;
if (a >= 0.5) {
d = 255; // dark colours - white font
}
return Color.argb(alpha, d, d, d);
}
I would have commented on the answer by #MichaelChirico but I don't have enough reputation. So, here's an example in R with returning the colours:
get_text_colour <- function(
background_colour,
light_text_colour = 'white',
dark_text_colour = 'black',
threshold = 0.5
) {
background_luminance <- c(
c( .299, .587, .114 ) %*% col2rgb( background_colour ) / 255
)
return(
ifelse(
background_luminance < threshold,
light_text_colour,
dark_text_colour
)
)
}
> get_text_colour( background_colour = 'blue' )
[1] "white"
> get_text_colour( background_colour = c( 'blue', 'yellow', 'pink' ) )
[1] "white" "black" "black"
> get_text_colour( background_colour = c('black', 'white', '#236FAB', 'darkred', '#01F11F') )
[1] "white" "black" "white" "white" "black"

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