A concept of the color is quite difficult by itself even if we are talking about single point (pixel) of the image. A definition of the color of the area that contains number of pixels is considerable more sophisticated as description of one person and population of town. One person has his height, crowd can be characterized by average value of heights, standard deviation and histogram of distribution.
Color of one pixel.
Physically color of one
point can be characterized by reading of three cone
neighbor cell detectors on retina of eye. Each of these detectors has its
own area wavelength sensitivity in spectra. Making very lazy simplification
one can named them red, green and blue receptors. Reading these sensors
sent to brain where normalized can be presented in form RGB
Blue) color space. Historically and for
pure convenience of manipulation in computers values
these prime colors are in range from 0 to 255 each.
Combination of these three numbers gives millions of different colors.
Other natural way to characterize
a color is not from point of view of observer but
characteristic of photons bean. Here will be simplification too,
sorry. One can describe ray of light with wavelength of photons, signal/noise
ratio and intensity and . There characteristics can be associated with
numbers named Hue, Saturation and B
rightness. Hue represent color by name itself and
lies in range 0-359. The range rightly hints that it is like
red, blue, green projectors illuminate circle screen in tree opposite
directions. So 0 and 359 of hue is neighbor colors. Strange. Saturation
measure how far the color are from grey, 0 grey, 100 is naive color. Brightness
shows a grade between black and white. From 0 for
black to 255 for white. In LeoPicture brightness is
just average of RGB values. Note that in other
approach brightness are defined as maximum of RGB
values. We don´t think that it is much sense
as soon pure pure red ,
and very pink for example
will have the same value of brightness 255. Not too
practical from our point of view. When we taken brightness
as average pure red had 85 and very pink around 240.
Color of object.
Here is unavoidable terminology confusion.
What is object? Is image of forest on the other side of pond a object? It is very subjective.
We defined an object here as a part of picture (whole picture in same cases) observer interested in. Pure practically.
LeoPicture presents all six described above characteristics
of color (Red, Green, Blue, Hue, Saturation, Brightness) inside selected
in form of raw statistical data - average, standard
deviation, histogram of distribution. on the picture
is shown an example for the Hue for selected part
of the picture:
By clicking on name of color
attribute user can invoke the histogram of its distribution
in intuitive self-explanatory manner.
and standard deviation of Hue is calculated taken
into account its tricky self bitten tail nature that
especially noticeable in area of gluing 0 with 360.
When color analyses tab is active user can change
selected area instantly observing updated histogram
of color characterization. Note that modification
of image in tab of common operation as doing selected
area brighter, contrasted, more colorful will not
affect result of analysis until they will be accepted.
A standard operation procedure of quality
control on the base of color can be described as following:
In picture of etalon sample of material most characteristic area will be selected and "Get current as standard" link clicked.
Then for image of each tried manufactured material select area that is fully inside. There will be two histogram overlapped one of standard and other of checked sample. Normalized in range 0 -100 coefficients of similarity by each of color characteristics will be calculated and displayed as well.
It will be up to user to investigate threshold of similarity
coefficients to establish pass value or some combinations of them.