我想设计一个程序，可以帮助我在5种预定义的颜色中评估哪一种更类似于可变颜色，以及与可变颜色的百分比。问题是我不知道如何手动一步一步地做到这一点。所以想一个程序就更难了。
更多细节:颜色来自不同颜色的管子和凝胶的照片。我有5个不同颜色的管子，每个代表5个等级中的1个。我想拍摄其他样本的照片，然后在电脑上通过比较颜色来评估样本属于哪个级别，我也想知道一个近似的百分比。我想要一个这样做的程序:http://www.colortools.net/color_matcher.html
如果你能告诉我该采取什么步骤，即使它们需要我手动思考和执行。那会很有帮助的。
当前回答
通过人类感知来比较两种颜色的最佳方法之一是CIE76。这个差值叫做e。当小于1时，人眼无法识别差异。
有一个很棒的颜色工具类ColorUtils(代码如下)，它包括CIE76比较方法。作者是苏黎世大学的丹尼尔·斯特雷贝尔。
从ColorUtils.class我使用的方法:
static double colorDifference(int r1, int g1, int b1, int r2, int g2, int b2)
r1,g1,b1 -第一种颜色的RGB值
r2,g2,b2 -您想比较的第二个颜色的RGB值
如果你使用Android，你可以得到这样的值:
r1 = Color.red(像素);
g1 = Color.green(像素);
b1 = Color.blue(像素);
ColorUtils.class作者:Daniel Strebel，苏黎世大学:
import android.graphics.Color;
public class ColorUtil {
public static int argb(int R, int G, int B) {
return argb(Byte.MAX_VALUE, R, G, B);
}
public static int argb(int A, int R, int G, int B) {
byte[] colorByteArr = {(byte) A, (byte) R, (byte) G, (byte) B};
return byteArrToInt(colorByteArr);
}
public static int[] rgb(int argb) {
return new int[]{(argb >> 16) & 0xFF, (argb >> 8) & 0xFF, argb & 0xFF};
}
public static int byteArrToInt(byte[] colorByteArr) {
return (colorByteArr[0] << 24) + ((colorByteArr[1] & 0xFF) << 16)
+ ((colorByteArr[2] & 0xFF) << 8) + (colorByteArr[3] & 0xFF);
}
public static int[] rgb2lab(int R, int G, int B) {
//http://www.brucelindbloom.com
float r, g, b, X, Y, Z, fx, fy, fz, xr, yr, zr;
float Ls, as, bs;
float eps = 216.f / 24389.f;
float k = 24389.f / 27.f;
float Xr = 0.964221f; // reference white D50
float Yr = 1.0f;
float Zr = 0.825211f;
// RGB to XYZ
r = R / 255.f; //R 0..1
g = G / 255.f; //G 0..1
b = B / 255.f; //B 0..1
// assuming sRGB (D65)
if (r <= 0.04045)
r = r / 12;
else
r = (float) Math.pow((r + 0.055) / 1.055, 2.4);
if (g <= 0.04045)
g = g / 12;
else
g = (float) Math.pow((g + 0.055) / 1.055, 2.4);
if (b <= 0.04045)
b = b / 12;
else
b = (float) Math.pow((b + 0.055) / 1.055, 2.4);
X = 0.436052025f * r + 0.385081593f * g + 0.143087414f * b;
Y = 0.222491598f * r + 0.71688606f * g + 0.060621486f * b;
Z = 0.013929122f * r + 0.097097002f * g + 0.71418547f * b;
// XYZ to Lab
xr = X / Xr;
yr = Y / Yr;
zr = Z / Zr;
if (xr > eps)
fx = (float) Math.pow(xr, 1 / 3.);
else
fx = (float) ((k * xr + 16.) / 116.);
if (yr > eps)
fy = (float) Math.pow(yr, 1 / 3.);
else
fy = (float) ((k * yr + 16.) / 116.);
if (zr > eps)
fz = (float) Math.pow(zr, 1 / 3.);
else
fz = (float) ((k * zr + 16.) / 116);
Ls = (116 * fy) - 16;
as = 500 * (fx - fy);
bs = 200 * (fy - fz);
int[] lab = new int[3];
lab[0] = (int) (2.55 * Ls + .5);
lab[1] = (int) (as + .5);
lab[2] = (int) (bs + .5);
return lab;
}
/**
* Computes the difference between two RGB colors by converting them to the L*a*b scale and
* comparing them using the CIE76 algorithm { http://en.wikipedia.org/wiki/Color_difference#CIE76}
*/
public static double getColorDifference(int a, int b) {
int r1, g1, b1, r2, g2, b2;
r1 = Color.red(a);
g1 = Color.green(a);
b1 = Color.blue(a);
r2 = Color.red(b);
g2 = Color.green(b);
b2 = Color.blue(b);
int[] lab1 = rgb2lab(r1, g1, b1);
int[] lab2 = rgb2lab(r2, g2, b2);
return Math.sqrt(Math.pow(lab2[0] - lab1[0], 2) + Math.pow(lab2[1] - lab1[1], 2) + Math.pow(lab2[2] - lab1[2], 2));
}
}
其他回答
请参阅维基百科关于色差的文章以获得正确的线索。 基本上，你想要在多维颜色空间中计算一个距离度量。
但是RGB并不是“感知上一致的”，所以Vadim建议的欧几里得RGB距离度量将与人类感知的颜色之间的距离不匹配。首先，L*a*b*是一个感知上均匀的颜色空间，delta度量是常用的。但有更精致的色彩空间和更精致的delta公式，更接近人类的感知。
你需要学习更多关于颜色空间和光源的知识来进行转换。但如果想要一个比欧几里得RGB度量更好的快速公式，只需这样做:
假设你的RGB值在sRGB颜色空间中 找到sRGB到L*a*b*的转换公式 将sRGB颜色转换为L*a*b* 计算两个L*a*b*值之间的delta
计算成本不高，只是一些非线性公式和一些乘法和加法。
The best way is deltaE. DeltaE is a number that shows the difference of the colors. If deltae < 1 then the difference can't recognize by human eyes. I wrote a code in canvas and js for converting rgb to lab and then calculating delta e. On this example the code is recognising pixels which have different color with a base color that I saved as LAB1. and then if it is different makes those pixels red. You can increase or reduce the sensitivity of the color difference with increae or decrease the acceptable range of delta e. In this example I assigned 10 for deltaE in the line that I wrote (deltae <= 10):
<script>
var constants = {
canvasWidth: 700, // In pixels.
canvasHeight: 600, // In pixels.
colorMap: new Array()
};
// -----------------------------------------------------------------------------------------------------
function fillcolormap(imageObj1) {
function rgbtoxyz(red1,green1,blue1){ // a converter for converting rgb model to xyz model
var red2 = red1/255;
var green2 = green1/255;
var blue2 = blue1/255;
if(red2>0.04045){
red2 = (red2+0.055)/1.055;
red2 = Math.pow(red2,2.4);
}
else{
red2 = red2/12.92;
}
if(green2>0.04045){
green2 = (green2+0.055)/1.055;
green2 = Math.pow(green2,2.4);
}
else{
green2 = green2/12.92;
}
if(blue2>0.04045){
blue2 = (blue2+0.055)/1.055;
blue2 = Math.pow(blue2,2.4);
}
else{
blue2 = blue2/12.92;
}
red2 = (red2*100);
green2 = (green2*100);
blue2 = (blue2*100);
var x = (red2 * 0.4124) + (green2 * 0.3576) + (blue2 * 0.1805);
var y = (red2 * 0.2126) + (green2 * 0.7152) + (blue2 * 0.0722);
var z = (red2 * 0.0193) + (green2 * 0.1192) + (blue2 * 0.9505);
var xyzresult = new Array();
xyzresult[0] = x;
xyzresult[1] = y;
xyzresult[2] = z;
return(xyzresult);
} //end of rgb_to_xyz function
function xyztolab(xyz){ //a convertor from xyz to lab model
var x = xyz[0];
var y = xyz[1];
var z = xyz[2];
var x2 = x/95.047;
var y2 = y/100;
var z2 = z/108.883;
if(x2>0.008856){
x2 = Math.pow(x2,1/3);
}
else{
x2 = (7.787*x2) + (16/116);
}
if(y2>0.008856){
y2 = Math.pow(y2,1/3);
}
else{
y2 = (7.787*y2) + (16/116);
}
if(z2>0.008856){
z2 = Math.pow(z2,1/3);
}
else{
z2 = (7.787*z2) + (16/116);
}
var l= 116*y2 - 16;
var a= 500*(x2-y2);
var b= 200*(y2-z2);
var labresult = new Array();
labresult[0] = l;
labresult[1] = a;
labresult[2] = b;
return(labresult);
}
var canvas = document.getElementById('myCanvas');
var context = canvas.getContext('2d');
var imageX = 0;
var imageY = 0;
context.drawImage(imageObj1, imageX, imageY, 240, 140);
var imageData = context.getImageData(0, 0, 240, 140);
var data = imageData.data;
var n = data.length;
// iterate over all pixels
var m = 0;
for (var i = 0; i < n; i += 4) {
var red = data[i];
var green = data[i + 1];
var blue = data[i + 2];
var xyzcolor = new Array();
xyzcolor = rgbtoxyz(red,green,blue);
var lab = new Array();
lab = xyztolab(xyzcolor);
constants.colorMap.push(lab); //fill up the colormap array with lab colors.
}
}
// -----------------------------------------------------------------------------------------------------
function colorize(pixqty) {
function deltae94(lab1,lab2){ //calculating Delta E 1994
var c1 = Math.sqrt((lab1[1]*lab1[1])+(lab1[2]*lab1[2]));
var c2 = Math.sqrt((lab2[1]*lab2[1])+(lab2[2]*lab2[2]));
var dc = c1-c2;
var dl = lab1[0]-lab2[0];
var da = lab1[1]-lab2[1];
var db = lab1[2]-lab2[2];
var dh = Math.sqrt((da*da)+(db*db)-(dc*dc));
var first = dl;
var second = dc/(1+(0.045*c1));
var third = dh/(1+(0.015*c1));
var deresult = Math.sqrt((first*first)+(second*second)+(third*third));
return(deresult);
} // end of deltae94 function
var lab11 = new Array("80","-4","21");
var lab12 = new Array();
var k2=0;
var canvas = document.getElementById('myCanvas');
var context = canvas.getContext('2d');
var imageData = context.getImageData(0, 0, 240, 140);
var data = imageData.data;
for (var i=0; i<pixqty; i++) {
lab12 = constants.colorMap[i];
var deltae = deltae94(lab11,lab12);
if (deltae <= 10) {
data[i*4] = 255;
data[(i*4)+1] = 0;
data[(i*4)+2] = 0;
k2++;
} // end of if
} //end of for loop
context.clearRect(0,0,240,140);
alert(k2);
context.putImageData(imageData,0,0);
}
// -----------------------------------------------------------------------------------------------------
$(window).load(function () {
var imageObj = new Image();
imageObj.onload = function() {
fillcolormap(imageObj);
}
imageObj.src = './mixcolor.png';
});
// ---------------------------------------------------------------------------------------------------
var pixno2 = 240*140;
</script>
如果你有两个颜色对象c1和c2，你可以比较c1和c2的每个RGB值。
int diffRed = Math.abs(c1.getRed() - c2.getRed());
int diffGreen = Math.abs(c1.getGreen() - c2.getGreen());
int diffBlue = Math.abs(c1.getBlue() - c2.getBlue());
你可以将这些值除以饱和度的差异(255)，你就会得到两者之间的差异。
float pctDiffRed = (float)diffRed / 255;
float pctDiffGreen = (float)diffGreen / 255;
float pctDiffBlue = (float)diffBlue / 255;
之后你就可以找到平均色差的百分比。
(pctDiffRed + pctDiffGreen + pctDiffBlue) / 3 * 100
这就得到了c和c之间的百分比差。
Android for ColorUtils API RGBToHSL 我有两个int argb颜色(color1, color2)，我想要得到两种颜色之间的距离/差异。这是我所做的;
private float getHue(int color) {
int R = (color >> 16) & 0xff;
int G = (color >> 8) & 0xff;
int B = (color ) & 0xff;
float[] colorHue = new float[3];
ColorUtils.RGBToHSL(R, G, B, colorHue);
return colorHue[0];
}
然后我使用下面的代码来查找两种颜色之间的距离。
private float getDistance(getHue(color1), getHue(color2)) {
float avgHue = (hue1 + hue2)/2;
return Math.abs(hue1 - avgHue);
}
对于快速和肮脏，你可以做到
import java.awt.Color;
private Color dropPrecision(Color c,int threshold){
return new Color((c.getRed()/threshold),
(c.getGreen()/threshold),
(c.getBlue()/threshold));
}
public boolean inThreshold(Color _1,Color _2,int threshold){
return dropPrecision(_1,threshold)==dropPrecision(_2,threshold);
}
利用整数除法对颜色进行量化。
