I would like to change smoothly the background color of a view over time.
Choosing 2 colors c1 and c2, it is easy in the rgb space to make a color function of the time c(t) = t.c1 + (1-t).c2, which will be a gradient between the two
However the rgb space is 3D and I am looking for a way to enumerate all colors smoothly.
I know there are billions of colors possible but coding RGB on 4x4x4 bits would be ok for my project.
My question is independent of the choice of the programming language
I have tried things like (pseudo code / Python)
for red in xrange(16):
for green in xrange(16):
for blue in xrange(16):
color = rgb(red, green, blue)
however this is not smooth at all, it is like a "step function" if you see what I mean (color will go from plain green to no green at all and a little red for instance)
Any idea how to do that ?
In that case I think you're better of with the HSV values of a color. You can use the same tactic and change only one of these HSV values at a time, to make the color shift more fluently.
Check this out (HSV)
EDIT:
After looking a bit further, I found this argument why NOT to use HSV.
This might be a good solution to your problem:
Solution
Related
I need to make a simple color picker. I have a slider that returns a floating point number between 0 and 1, which I'd like to convert into a color in the manner that you typically see in a color line or color spectrum (red on the left, violet on the right, green and yellow somewhere in the middle).
It seems like there must be some algorithm for converting the liner value into RGB values, but I can't find one. I've tried a few things on my own that did not really work.
I don't need anything super accurate or comprehensive, just something where the user can dial in an approximate color by sliding the slider left and right.
In the material color tool there is a place where you choose the primary color and it shows you the text color on primary.
Given a color in hexadecimal string, how to know what will be the suggested text color on that color?
e.g.
Some colors will suggest that the text should be black
Others will say that it should be white
Observation: Any language is ok, just want to know what is the logic / function to do it.
They wrote something about text legibility. Apart from that, I played around a bit. It seems like it's a weighted mean of the r,g,b parts of the color. Blue has significantly moreimpact than green, which has slightly lessimpact than red. So it is probably something like (1*r + 0.9*g + 1.2*b) / 3.1 > 0xff (2.85 is the sum of the weights). If it surpasses the threshold, the text is black, else it is white.
In react's material-ui they have a "formula" to create it, which uses the same logic as material components.
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 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.
Is there an algorithm (I've searched and haven't come up with much) that, given a hex value, is capable of returning the color name? It doesn't have to be anything too specific, any shade of blue coming back as just 'blue' is fine.
Or short of that, is there a large list somewhere that consists of hex values and their corresponding color family. I've found lists, but they only seem to be a couple hundred colors long.
I saw this post, but the solution there seems to only break the color down into three regions.
EDIT
I altered the RGB text file so that each color would only fall into the following color ranges:
white
grey
magenta
brown
black
blue
green
turquoise
yellow
orange
red
As you said you had already found lists, then it is simple.
Calculate Euclidean Distance of the color for RGB (for instance), and call that color the nearest name.
By the way, over a hundred colors is actually a big number for human languages, and even for just a hundred colors, ordinary people may not able to tell the differences between quite a few colors.
rgb.txt is the usual list used for color names. Just find the closest triplet and call it that.