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Similarity Between Colors
I know it's not a programming question but I think the understanding of the color models is always bound to a programmer's life.
So we were having an argument about a certain color in the office. I was saying that a particular color was more near to pink and a colleague said it was more close to purple.
The question is how can I measure the distance of a color from another color?
Example:
Pink=(255, 192, 203) -->A
Purple=(128, 0, 128) -->B
Color in question=(232,143,253)-->C
The A or B is closest to C?
A simple method is to calculate the Euclidean distance in the RGB cube using the formula:
√((r2-r1)2 + (g2-g1)2 + (b2-b1)2)
However this won't accurately measure the human perception of closeness. For example, the human eye is more sensitive to some colours than others. To take this into account you will need to look at some research on the topic of human perception of colour. This Wikipedia page has some good starting points: Color difference
Related
I have to find the nearest color. For example, I have two colors colorA1, colorA2 which are nearly same color. And also I have other color colorB1.
And I need such a method:
Color getNearestColor(colorA1, colorA2, colorB1). This method should give me the colorB2 which is calculated by using the difference of colorA1 and colorA2, then using their distance it should give me colorB2 which has the same distance as in colorA1 and colorA2.
Can you give some ideas how to implement it?
To find the nearest colour, you need a definition of "near", so a metric.
In Wikipedia you will find different metrics of color differences.
Personally I would use the 2*R*R + 4*G*G + 3*B*B. (no need for square roots, you will just compare same metrics). Easy to calculate, you can use just integers (if you use 32 bit integers, you will have no overflow).
Then find which colour has the smallest differences between your target colour.
The other methods are more precise, but in that case "RGB" is not enough. You need to know which colour space are using (probably you are in sRGB).
What is the relationship between color spaces (RGB, XYZ) and the color matching function? Let's say we have some color matching function in the color space XYZ (3 row matrix). We also have the transformation matrix which translates from XYZ coordinates to RGB coordinates.
My understanding is that there is some visual input, which is made up of the color spectrum S(y). The human eye does not see the world - it only sees its interpretation of the world. The human eye has 3 cone types LMS, each of which is responsible for processing RED, GREEN, or BLUE. The human eye sees the spectral color only because it's eye sums over RED, GREEN, BLUE vector, and this sum matches the color of the input. In order to match the color, there is a color matching function, which takes the input spectrum and produces the weights by which to multiply the primary RED, GREEN, BLUE color vector. These then get added and their output visually matches the spectral input, even though the spectrum had many many frequencies added, while the human eye was only adding 3. So we went from HUGE space to space where we can describe all with 3 vectors, summed as dictated by the color matching function.
The spectral input, color primaries, and color matching functions behave as described above and can be summarized in this formula:
where pi is the 3d vector of primary colors, c - color matching function is also a vector of 3 components, and finally s is the spectral input.
We have XYZ color space, and a corresponding color matching function which does what is described above. We are then given matrix T, which transforms XYZ coordinates to RGB coordinates. We already know T, and we need to use it to produce a new color matching function for the RGB color space.
I do not understand how the color space relates to choice of primaries pi(λ) and the choice of color functions ci(λ1).
I have been trying to understand about colours from months and after some research, i believe I have some insights which probably can help me answer your question.
I do not understand how the color space relates to choice of primaries
pi(λ)
Primaries are nothing but the wavelength of the colors that we choose to use for making all the other colors in space and that also defines the gamut of the colour space. So if you play with the applet provided in the link that is given below you can see that the whole gamut in the colour space changes when you change your primary.
Have a look at Alternative primaries and gamuts section.
Now I do not know how much you understand the RGB and XYZ or what do you mean when you say RGB here (assuming you are referring to sRGB gamut values); XYZ are actually Tristimulus values which are called rho, beta and gamma as shown in the image above and just for simplicity XYZ are converted to xy space from where you get your standard sRGB gamut.
Please go through this if you are interested in understanding how colour sensors work and converting sensor values to XYZ matrix
Please comment if I have missed any information or answer needs editing.
I think lots of issues with color selection are due technical problems people had to solve. Usually you are not trying to reproduce colors as accurately as possible, but to make them pleasant looking, cheap, fast to calculate on cpu.... If someone watches plains of New Zealand on TV he is very unlikely to know they really look like, but almost certainly wants to enjoy the picture and pay little for it.
Several reasons why you might want to use different color matching functions might include:
You are taking pictures under non-white light and you want your picture to look natural.
You are taking underwater pictures and want to compensate for the fact that water attenuates different frequencies at different speeds.
Your sensor is not perfect and you want to compensate for that.
On the other hand you might want to change your primaries due to some reason. For example your images might be taking a picture of a scene with limited amount of colors. By nudging your primaries a little you might get a "fuller" picture.
Finally sometimes you just have to compensate for some of the limitations you have with your devices. Your phosphorus on CRT TV will impose some restrictions. So will the noise in air when transmitting using PAL. On the other hand if you go digital you might be forced to have less than 36 bits per pixel. In that case you will have to make compromises and this will give you opportunity to lose as little as possible.
If you want a short tutorial visit Cambridge in colour.
Here is a Szeliski's textbook on photography, look at chapters 1 2 and 10.
Poyton has list of common transformations.
I'm trying to make a bar with gradient color updownward, I set 3 points as stated in the bar. Now the picture seems good, but I don't know how to automatically generate these color mathematically, by RGB or HSB? I'm having trouble with the rule of this kind of art thing.
I was intending to do it with RGB but I found it hard to do. But with HSB, I changed "S" and it makes a little sense as shown in picture.
My question is: How to calculate these three colors based on ONE given color, makes the gradient natural?
Thanks in advance, this has nothing to do with code but I think it definitely has a mathematical solution(formula).
I think there's no general rule for how to do this and different possibilities to get to a (subjectively pleasing) result.
I copied your colors here for analysis but didn't find a pattern in your choice. My solution would be to find a pleasing distance of (relative) luminance. To adabt to your example I chose one arbitrary color, then increased the Lum value by 18% for the second color and for the third one I subtracted 10% Lum again.
Do you like this solution?
I have two color values in HSI (Hue Saturation and Intensity) and I want a number which represents the visual difference between the two colors. Hue is a number between 0 and 360 inclusive. Saturation is 0 to 1 and Intensity is 0 to 1.
Lets consider for example Red and Blue at Saturation of 100% and Intensity of 100%.
At this website is a way to display the color by entering in the following text.
red is:
hsv 0, 100%, 100%
blue is:
hsv 240, 100%, 100%
Clearly these are two very different colors, and so a simple way I could try to calculate the difference between colors is to use the Hue component and calculate the absolute difference in hue which would be 120 (360-240) since 360 is also equal to 0 in hue.
The problem arises where the Saturation or Intensity is very dark or light, consider a very dark red and blue.
dark red is:
hsv 0, 100%, 20%
dark blue is:
hsv 240, 100% 20%
Obviously the visual difference between these two colors is less than the bright red and blue colors, as a human would state if asked to compare the differences. What I mean here is, ask a friend "Which pair of colors is most different?" they will likely say the top bright red blue.
I am trying to calculate the difference between two colors as a human would notice. If a human being looked at two colors a and b, then two colors c and d, he could notice which ones are the most different. Firstly if the colors are bright (but not too bright) then the difference is hue based. If the colors are too bright such as white or too dark such as black or too grey then the differences are smaller.
It should be possible to have a function diff where x=diff(a,b) and y=diff(c,d) yields x and y, and I can use x and y to compare the differences to find the most different color or least different color.
The WCAG2.0 and 1.0 guidelines both make reference to different equations on perception of color difference:
contrast ratio (http: //www.w3.org/TR/2008/REC-WCAG20-20081211/Overview.html#contrast-ratiodef)
brigtness difference and 3. color difference (http://www.w3.org/TR/AERT#color-contrast).
I tried the Delta-e method(http: //colormine.org/delta-e-calculator/) but it is quasimetric so the difference measurement may change depending on the order you pass the two colors. If in your example you expect diff(a,b) to always equal diff(b,a) then this is not what you want(there may be different algorithms under this name that aren't quasimetric but I haven't looked into it past that site).
I think that the color difference metric is the closest to matching my expectations of color difference measurements. For your example it will yield that diff(a,b) > diff(c,d)
You can test it out for yourself using the tool at this website: http://www.dasplankton.de/ContrastA/
The general answer seems to be what David van Driessche said, to use Delta E. I found some Java code here: https://github.com/kennyliou/GAI
This is a answer to the question, may not be the best answer.
Let's say that I have a list of valid color values like [0x67FF82, 0x808080, 0xffffff, ...] and given an input color, in hex, I want to find which color in the list of acceptable colors that the input color is closest to.
My thought is that I'd find the color in which the absolute value of the difference of the red, green, and blue values is smallest. Is this correct?
It sounds like you're looking for a way to quantify the "distance" between colors - in math, they'd call it a metric. Many people are intuitively pretty comfortable with the Euclidean metric for example - it's simply the distance between two points as measured with a ruler. In the case of colors, things are more complicated because of subjective perception of different colors.
There's a pretty mathy wikipedia article about color difference, which includes links to different implementations.
The difference or distance between two colors is a metric of interest in color science. It allows people to quantify a notion that would otherwise be described with adjectives, to the detriment of anyone whose work is color critical. Common definitions make use of the Euclidean distance in a device independent color space.
In particular, there's Python Colormath, an implementation in python that converts between different color encodings and also seems to have a function for calculating the distance between two colors. If you happen to be coding in python, that sounds helpful, although I unfortunately don't have any personal experience with that tool. There's also similar resources available for MATLAB and Excel provided by the authors of CIE2000, a leading color-difference formula.