colorsdistancemetricshsv

Calculate distance between colors in HSV space

I intend to find a distance metric between two colours in HSV space.

Suppose that each colour element has 3 components: hue, saturation, and value. Hue is ranged between 0 to 360, saturation is ranged between 0 to 1, and value is ranged between 0 to 255.

Also hue has a circular property, for example, 359 in hue is closer to 0 in hue value than 10 in hue.

Can anyone provide a good metric to calculate the distance between 2 colour element in HSV space here?

Solution

  • First a short warning: Computing the distance of colors does not make sense (in most cases). Without considering the results of 50 years of research in Colorimetry, things like the CIECAM02 Color Space or perceptual linearity of distance measures, the result of such a distance measure will be counterintuitive. Colors that are "similar" according to your distance measure will appear "very different" to a viewer, and other colors, that have a large "distance" will be undistinguishable by viewers. However...

    The actual question seems to aim mainly at the "Hue" part, which is a value between 0 and 360. And in fact, the values of 0 and 360 are the same - they both represent "red", as shown in this image:

    Hue

    Now, computing the difference of two of these values boils down to computing the distance of two points on a circle with a circumference of 360. You already know that the values are strictly in the range [0,360). If you did not know that, you would have to use the Floating-Point Modulo Operation to bring them into this range.

    Then, you can compute the distance between these hue values, h0 and h1, as

    hueDistance = min(abs(h1-h0), 360-abs(h1-h0));

    Imagine this as painting both points on a circle, and picking the smaller "piece of the cake" that they describe - that is, the distance between them either in clockwise or in counterclockwise order.

    EDIT Extended for the comment:

    So imagine you have two HSV tuples. Call them (h0,s0,v0) and (h1,s1,v1). Then you can compute the distances as follows:

    dh = min(abs(h1-h0), 360-abs(h1-h0)) / 180.0
ds = abs(s1-s0)
dv = abs(v1-v0) / 255.0

    Each of these values will be in the range [0,1]. You can compute the length of this tuple:

    distance = sqrt(dh*dh+ds*ds+dv*dv)

    and this distance will be a metric for the HSV space.