Processing: Creative Coding and Computational Art

PROCESSING: CREATIVE CODING AND COMPUTATIONAL ART
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Not everyone seems to be able to see these often subtle color relationships. Squinting or
crossing your eyes, turning an image upside down, or changing your viewing distance to an
image are techniques that can sometimes help you to better see these phenomena. I’ve
had very bright, talented students really struggle when it came to seeing and mixing color,
while other students seem to take to it very naturally. It’s led me to believe that, just as
some people can more naturally distinguish subtle modulations in pitch (I’m not one of
them), there is a similar mechanism for perceiving and differentiating color. However, I
feel it’s also important to point out that great art has been created by both strong and
weak colorists. Some artists/art professors even believe that innate gifts, such as color sensitivity
or drawing facility, can even at times impede a person’s development as an artist.
So if you can’t see the color shift in the example, try not to freak out.
Color has three distinctive properties: hue, value, and chromatic intensity. Hue relates to
the actual names we associate colors with (red, green, blue, etc.). Hue is controlled by the
wavelength of the light. For example, the hue of a ripe lemon is yellow, while the hue of a
stop sign is red. An object absorbs all the colors in the visual spectrum (light) except the
color we perceive reflected back to our eyes. Thus, a red object absorbs all the colors
except red.
Value relates to the brightness vs. darkness of the color. Value is also strongly determined
by light. Although it is possible to shift the hue of a color, as in the last example, it can only
be shifted so far in the physical world. However, the value of a color has less constancy.
The value of the color on an orange’s surface is drastically different in a dark room than
outside in the sun. Value often confuses people when first learning about color. When
looking at an object, they tend to see what they know about an object—which is usually
primarily defined by the hue. For example, if I create a still life and place an egg in shadow
next to an eggplant under a light source, most beginning art students will assume the egg
surface has greater value than the eggplant, as they associate white with brightness and
the eggplant’s dark purple as darkness. Under the same exact lighting conditions, an eggplant
would be darker than an egg, so the gestalt function in our mind codes a predictable
pattern, which usually holds true, until some sneaky art professor sticks an eggplant under
a bright lamp.
The last component of color is chromatic intensity. Two colors can have similar hue and
value, but very different chromatic intensities. Consider the difference in color between a
brick and an orange. The hue in both is orangish, and the value could be very similar, but
there is still a difference in the color, which is controlled by chromatic intensity. When a
color loses some of its chromatic intensity, we speak of it getting neutralized or moving
toward gray. In the artist’s color wheel, which we’ll look at next, certain colors have a complimentary
relationship. When two complimentary colors mix, they neutralize each other,
reducing the chromatic intensity of each. Before you look at the color wheel, I want to
make sure you understand the syntax in these two lines of code:
color swatch = color(100, 100, 120);
fill(swatch);
color is a Processing data type. The function call color(100, 100, 120) returns a color
value, which I assigned to the variable swatch, declared of the type color. The three arguments
I passed to the color function represent the red, green, and blue components of