The Scarcity of Universal Colour Names

Gunilla Borgefors

Centre for Image Analysis, Dept. of Information Technology, Uppsala University, Sweden

Keywords: Colour Names, Basic Colour Terms, Colour Perception, Deep Learning, Image Retrieval, Image

Annotation.

Abstract: There is a trend in Computer Vision to use over twenty colour names for image annotation, retrieval and to

train deep learning networks to name unknown colours for human use. This paper will show that there is

little consistency of colour naming between languages and even between individuals speaking the same

language. Experiments will be cited that show that your mother tongue influences how your brain processes

colour. It will also be pointed out that the eleven so called basic colours in English are not universal and

cannot be applied to other languages. The conclusion is that only the six Hering primary colours, possibly

with simple qualifications, are the only ones you should use if you aim for universal usage of your systems.

That is: black, white, red, green, blue, and yellow.

1 INTRODUCTION

Under ideal conditions, humans can perceive over

four million different colours. But how many can we

consistently name?

This question is important when computer vision

and pattern recognition interacts with humans and

colour is involved. Examples are using deep learning

(or other methods) to name unknown colours or,

more frequently, to use colour names for image

annotation and retrieval. A seminal paper is (van de

Weijer et al., 2009) that uses up to 22 English colour

names for these purposes. This paper has been much

cited and the many colour names in it are often used.

However, the colour names people use are not

universal and depend on many circumstances, e.g.,

the culture and language in which the person grow

up and her interests and hobbies. I will show that

there is very little consensus on how to name the

parts of the human colour gamut. What is azure to

one may be simply blue to another and be the same

colour as grass to a third. There is even clear evi-

dence that your mother tongue influences how your

brain processes colour, even when no naming is

involved.

In view of the non-consensus of colour names,

the trend of using many colour names in computer

vision and pattern recognition becomes problematic.

How meaningful are the deeply learned names

for people who were not themselves first trained to

“correctly” name the colours the researchers chose?

How well will images be retrieved if users are allow-

ed to freely use their own colour names or do not

understand the imposed English names? These are

the questions this paper aims to answer.

When discussing colour names most linguists use

the Munsell colour chips, Fig. 1. Colour hues are

divided into 40 steps, denoted 1-40 from red to red,

and for each hue there are eight lightnesses denoted

B-I. Saturation is always maximal. A greyscale in

ten steps, A-J, is also included. There are thus 330

chips.

Each colour name has a focus, i.e., the most typi-

cal Munsell chip for that colour; and a range, i.e. all

chips that can be called that colour.

Section 2 will briefly describe human colour

vision, historical and current colour linguistics, and

give an insight in personal colour names. Section 3

will describe three experiments that show that your

colour naming system influences how your brain

responds to colour stimuli. Finally, Section 4 will

contain conclusions and recommendations.

2 COLOUR NAMING

2.1 Human Colour Vision

Humans have three colour opsins in the retina,

S(hort), M(edium), and L(ong), where length refers

496

Borgefors, G.

The Scarcity of Universal Colour Names.

DOI: 10.5220/0006649004960502

In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2018), pages 496-502

ISBN: 978-989-758-276-9

to light wave-length. S, M, and L cones are most

sensitive to purple, green, and greenish yellow,

respectively. The signals from the three opsins are

combined in the retina before they are sent on to the

brain in three channels: the M+L channel that

measures “lightness;” the M-L channel that mea-

sures “redness;” and the S-(M+L) channel that

measures “blueness.”

Ewald Hering studied human colour vision and

came up with six “Urfarben” (primary colours),

(Hering, 1878). He based these on his knowledge of

human perception and our “ghost” colour after

images. After having stared for a time at a red square

on a white background, we briefly see a ghostly

green square when the red one is suddenly removed.

The same is true for blue/yellow and white/black.

These three pairs are closely linked to the three

colour channels in the optic nerve, even though they

had not been discovered at that time.

2.2 Early Colour Linguistics

The study of colour names across time and cultures

started in the second half of the 19

century (Big-

gam, 2012). The first publication was (Gladstone

1858) (written while William Gladstone took a break

from British politics). He was intrigued by the scar-

city of colour terms, and the strangeness of those

used, in Homer’s works (e.g., green honey, violet

sheep). Lazarus Geiger, how knew very many anci-

ent and modern languages, made the same obser-

vation for Indian Vedic Poems in Sanskrit; Old

Testament in Hebrew; Quran in Arabic; and Sagas in

Icelandic (Geiger, 1869). The general conclusion,

made possible by the recent theory of evolution, was

that full colour vision had evolved very recently in

human history.

At this same time linguists, anthropologists, and

missionaries studied the languages of “primitive”

tribes and discovered that many of them had few and

confusing (to the Europeans) colour concepts, just as

the ancients. Therefore it was concluded that they

had not developed full colour vision either.

After a train accident in 1875 Sweden, that was

caused by a colour-blind driver mistaking the red

stop signal for green, Fritiof Holmgren (Holmgren,

1877), devised a simple test for colour blindness,

using differently coloured yarns. The test became

widely used, not only to improve traffic safety, but

also to determine that “primitive” people had perfect

colour vision.

The conclusion was that colour naming

completely is random and only depends on culture.

Research in colour linguistics stopped for a long

time. However, all humans that have all three colour

opsins have very similar colour perception. Should

that not lead to similarities in how the colour space

is divided?

2.3 Basic Colour Terms

In 1969 the area of colour linguistics restarted with

(Berlin and Kay, 1969). Their study was based on

many, mostly North and South American, languages.

A key concept is the Basic Colour Terms (BCT)

present in a language. A BCT should fulfil many

conditions, the most important being:

• Meaning is not understood from itself (yellow vs.

lemon)

• Cannot be contained in a larger category (red vs.

scarlet)

• Can be used for everything (yellow vs. blonde)

• Consensus among native speakers

• Adapts to grammar (greener vs. “avocadoier”)

• High frequency in speech and writing

• Not a recent loan word

• Short response time for naming

The very few languages with only two BCTs only

distinguish dark/cold colours from light/warm

colours. The Dani in New Guinea use such a lan-

guage, where mili is used for black, dark and cold

colours with focus in dark blue or dark green; and

mola is used for white, light and warm colours with

focus in pink or dark red, (Heider, 1972).

A much earlier study (Almqvist, 1883) of the

Chukchis of Siberia discovered that they had three

BCTs (although the term was not used then): nukin,

focus black, nidlikin, focus white, and tschetlju,

focus red.

Based on the conditions above, place names from

a road atlas (Motormännen, 2011) and plant names

from a flora (Lid, 1974) I consider my own language

Swedish to have eight BCTs. In place names the

colours black, green, and red are most common,

while for plants names they are yellow, white, and

blue. Grey and brown are also significantly present

in both categories. All other colours are very rare.

The Americans Berlin and Kay took English as

the standard for all languages and identified eleven

BCTs. In addition to the eight Swedish ones they list

pink, orange, and purple, see Fig. 1 again for English

BCT foci. All languages investigated so far has from

two to twelve BCTs – eleven is not universal.

Regularities between languages that cannot be

explained if colour naming is completely random

were described in (Berlin and Kay, 1969), but some

of the conclusions have been superseded by later

studies including more languages, see the next Sub-

section.

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497

2.4 The World Colour Survey

After the restart of colour linguistics researchers

went all over the world collecting colour naming

systems from as many languages as possible using

the Munsell chips in a standardized way. In 2009 the

World Color Survey was published (Kay et al.,

2009) (the same Paul Kay 40 years later), presenting

the results for 110, mostly pre-industrial, languages

from all over the world. For each language the focus

and range for all BCTs, as roughly agreed by a

number of informants, are marked on the chip chart.

Note that in the following I use English colour

names, like black, not as BCTs, but as rough indi-

cations of the colour ranges of the BCTs of different

languages.

Languages are divided into five stages, I-V,

depending on the number of BCTs. Stage I have two

BCTs and stage V six or more.

There are no Stage I languages in the World

Colour Survey, but several Stage II. The amazing

discovery is that all of them divide the chips in

roughly the same way, into black, white, and

red, just like the Chukchi. An example is shown in

Fig. 2. If colour naming was completely random,

this would not be the case.

Languages with four BCTs divide colour space

in different ways, but the divisions are still not ran-

dom. Except for a very few cases, all languages

follow one of five “paths,” A-E, see Fig. 3.

The most common Stage III is III

which have

white and red, but divides black into black and

“grue.” Including both green and blue colours in a

single BCT is so common that linguists have invent-

ed the term grue to denote it.

The other common possibility for Stage III,

III

, is to divide red into red and yellow and

keep all dark, cold colours together. Indications

show that Proto-Indo-European, that was spoken on

the steppes north of the Black and Caspian Seas

about 10,000 years ago and is the ancestor of almost

all European and many Middle East and Indian lan-

guages of today, was Stage III

(Biggam, 2012).

There are also a few Stage III

languages where

the four BCTs are white, black, red, and “every-

thing else,” see Fig. 4.

In Stage IV

yellow is split from red. In Stage

black splits into black and grue, while in

Stage IV

black is divided into black and green.

This is how the Vikings talked: all dark and blue

colours were called “blå,” i.e., blue. Thus they called

Africa “Blueland” where the “blue men” lived!

Figure 3: The five paths of colour naming that describes

almost all of the very many languages investigated. See

the text.

Stage IV

is IV

again, while IV

divides the

“everything else” into blue and yellow+green.

Finally all Stages join in V, where all the Hering

primaries are BCTs. With more BCTs there is so

little regularity that all attempts of finding “paths”

have been abandoned.

It should perhaps be noted that grey is a special

case, which can be present as a BCT in earlier

Stages than V.

Thus it does seem that human vision has an

influence on colour naming after all, as in all known

languages with enough BCTs the Hering primaries

are BCTs. Also, the borders between BCT ranges

tend to be in about the same places, when they are

present at all.

2.5 Blue

As already mentioned, many languages place green

and blue colours into one BCT, denoted grue. This is

the case for all Celtic languages, e.g., Welsh, Irish,

and Breton and many African ones, like Bété and

Zulu. Until very recently Japanese was also a grue

language, although it seems at present to be moving

towards separation. Of course green and blue can be

distinguished also in grue languages, by, e.g., saying

“grue like grass” and “grue like sky.”

A few languages with twelve BCTs exist, to the

English-speaking linguists’ surprise. The most cited

example is Russian, which divides English BCT

blue into синий (siniy) for dark blue and голубой

(goluboy) for light blue. As we will see later, this

divide actually influences Russian brain organisa-

tion. Linguists seem not completely convinced, but

Italian blu (dark blue) and azzurro (light blue)

should perhaps also be considered BCTs? Another

twelve BCT language is Hungarian that separates

English BCT red into dark red and light red.

The paper that inspired this one (van de Weijer et

al., 2009) lists blue, cyan, turquoise, and azure as

useful blue terms among their 22 colour names.

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(Strangely not indigo, that is traditionally one of the

colours of the rainbow.) Only blue is an English

BCT while the other three are included in the blue

BCT range. Having one colour term that includes

three others, and then considering all four separate is

both illogical and confusing.

2.6 Personal Colour Names

In the previous Subsection differences between lan-

guages were discussed. In this one the focus is on

differences between individuals. The colour names

used vary considerably within the same language

depending on age, sex, education, being mono- or

multi-lingual, urban or rural... So, how many colour

names does a person usually use? And how many

colours can they remember?

One way of sorting colour names is dividing

them into four groups: 1: BCT (green), 2: qualified

BCT (dark green), 3: qualified fancy (spruce green),

and 4: fancy (avocado), (Biggam, 2012).

It is often said that women are better at colours

than men. A 1977 American study (Rich, 1977)

using 25 Munsell chips showed that men and nuns

mostly use categories 1-2, while other women

mostly use categories 3-4. Other studies have

showed similar results. Just like the scholars in the

century thought the ancients colour-blind, this

has resulted in the myth that women have better

colour vision than men. This is as false as the earlier

myth. That colour blindness is more common in men

and a few rare women do have superior colour

vision (Jameson et al., 2001) does not affect the

waste majority of both sexes that has normal colour

vision.

Two more recent studies of young people have

showed no sex differences for university students

and teenagers in USA (Smith et al., 1995, Machen,

2002), so this difference between the sexes may be

disappearing. Earlier sex differences are thought to

reflect women’s greater interest in colours for hob-

bies and appearance.

An interesting study is (Derefeldt and Swartling,

1995) that addresses colour naming and colour

remembering. The purpose was to investigate how

many colours a person can remember correctly, if

they are allowed to name the colours themselves. In

the learning session the subjects were shown a set of

35 colour chips on a normalized colour display and

asked to name and remember each colour. In the

identification session only one colour was shown on

the screen and the subjects asked to name it. The

subjects could then correctly identify 30-35 colours,

with a median of 32.5.

This was a study where subjects were allowed

about half an hour for training. Other studies have

showed that with intense training it is possible to

remember many more colours (Derefeldt, 2007), but

it could be argued that this study shows the approxi-

mate number of remembered colours for the average

person. If everybody agreed on the same thirty

colours the over twenty in (van de Weijer et al.,

2009) would be reasonable, but this is not the case.

Also interesting are the names used by the sub-

jects in the study. It was done in Swedish, so they

are translated here and in the report. The only un-

qualified BCT (group 1) used was brown. Qualified

BCTs (2) were also rare, but a few like “dark yel-

low” and “medium grey” were used. The most

common category was qualified fancy (3), e.g., “flag

blue,” “pigeon blue,” “thunder blue,” and “midnight

blue.” The oddest was “Elvis green” (from the cover

of an Elvis record). There where also some fancy

names (4), such as “cerise,” “plum,” and “jade.”

Some names were obviously invented during the

test, showing that the subjects did not have enough

colour names in their vocabularies for the 35 chips.

Another observation is that the authors Derefeldt

and Swartling use the English BCTs without com-

ment even though they are not suitable for Swedish.

The most obvious problem is the authors’ attempts

to squeeze the many different colour terms for

“blue-red” used by the subjects (showing there is no

suitable Swedish BCT here) into the English BCT

purple. There were also problems with English BCT

pink, which one subject called “white-red.” Even

though this is a single case, further investigations

would probably show that many other modern

languages do not fit in the English Procrustes bed.

3 EXPERMENTS

3.1 Russian Blues

In this experiment (Winawer et al., 2007) English

and Russian subjects were shown a big blue square

with two smaller blue squares beneath it, see Fig.5

left. The task was to, as quickly as possible,

determine if the left or right small square was equal

to the big one. For English subjects, for whom all

colours were covered by the BCT blue, the decision

time was linearly dependent on the distance between

the colours: the more different the colours the faster.

For Russians, for whom the lighter blues are in BCT

goluboy, while the darker ones are in BCT siniy, the

results were different. They were faster when the

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499

colours were in different BCTs even if the colour

distance was the same as within a BCT.

The test was repeated, but this time the subjects

had to repeat out laud a string of random numbers,

thus occupying the brain’s linguistic centre. This

time, also the Russians’ decision times were depen-

dent only on colour distance. The linguistic classifi-

cation of colours does determine how the colours are

perceived, even when no names are involved.

Figure 5: The set-up for the “Russian blues” (left) and the

“Brain divided” (right) experiments. From (Winawer et

al., 2007) and (Gilbert et al., 2006).

3.2 A Brain Divided

Most language processing is done in the left hemi-

sphere of the brain. Therefore, (Gilbert et al., 2006)

devised a test to see if there is a difference between

the hemispheres regarding colour perception.

As they had English subjects, they used the

green-blue BCT border instead of the siniy-goluboy

one, but otherwise the test was similar to the previ-

ous one. A ring of small green or blue squares, see

Fig. 5 right, were shown to one hemisphere of the

brain (this is not very difficult to arrange, as the left

half of the retinas of both eyes communicate with

the right hemisphere and vice versa). In this way,

they could investigate if language has an influence

on colour handling even when using only one lan-

guage. One square was different and the task was

again to determine if it was on the left or the right

side of the ring.

The results were clear. When the left hemisphere

saw the colour patches, the response time was short-

er when the two colours were on different sides of

the blue-green border, while no such difference was

noticeable for the right hemisphere. Again, proof

that your mother tongue influences how your brain

processes colour.

3.3 In Focus or Out

In the previous tests response time was used as a

measure of brain activity. In the experiment by (Tan

et al., 2008) brain activity was measured directly

using Magnetic Resonance Imaging of the subjects’

brains. The language used was Mandarin Chinese.

The experiment used six colours: red, green, and

blue, that are BCTs in Mandarin, close to their foci

and thus easy to name; and “brown,” “grey,” and

“beige” that are not Mandarin BCTs and difficult to

name, see Fig. 6.

First, two squares were shown for a split second

and the task was to determine if they were equal or

not by pressing a button. No language task was thus

involved. For the easy to name BCTs two small

areas in the cerebral cortex of the left hemisphere

were activated, while for the non-BCTs those areas

were inactive.

In the second test, the subject was shown one

colour and asked to say the name out loud. This

time, the two previously identified small areas in the

cortex lit up brightly, thus being very active, for all

colours. They are apparently the areas in the brain

most involved in colour naming. The test shows they

are involved in colour processing of BCTs, but not

other colours, even though no colour naming task is

going on!

The conclusion of the three experiments is that

speakers of different languages probably do perceive

colours slightly differently, after all. Gladstone and

his contemporaries did have a point, not because of

different colour vision, but because different cultures

and languages wires our brains differently.

Figure 6: The colours used in the Chinese MRI brain acti-

vation test. From (Tan et al., 2008).

4 CONCLUSIONS

I have showed that colour foci and ranges vary con-

siderably between cultures and languages, even

though the divisions between BCT ranges are similar

when they occur al all. I have also shown the colour

names we use vary a lot between individuals even in

same culture. The (Derefeldt and Swartling, 1995)

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study shows as a meta-result the dangers of using the

eleven English BCTs as universals.

The experiments cited shows that the colour

naming system we grew up with even has con-

sequences for brain organisation, thus influencing

our colour processing and perception.

When using colour names in computer vision

and pattern recognition applications involving per-

sons not specifically trained to recognize and name

the colours used, it is thus best to stay with very few

colours. The Hering primaries seem safe enough.

It should also be remembered that although a

trained person can remember and identify up to 500

colours, a stressed human can identify only three or

four colours (Derefeldt, 2007). The latter discovery

has, e.g., influenced the designs of displays in

fighter aircraft.

It is, by the way, probably no coincidence that

the basic heraldic colours used over the centuries in

Europe and elsewhere – or (gold/yellow), argent

(silver/white), azure (blue), gules (red), sable (black)

and vert (green) – are exactly the Hering primaries.

Experience had shown that these colours were easy

to distinguish, especially since only metal on colour

or vice versa was allowed.

Qualifying the six primaries using lightness and

saturation is probably also safe, e.g., “light green”

and “dark green,” or “vivid red” and “dull red.”

Repeating the questions from the Introduction:

How meaningful is it to use many colour names in

applications intended for general, untrained, users?

It will not be clear for everybody which Munsell

chips can be called “azure,” especially if you mother

tongue is not English – and is English azure the

same as Italian azzurro? Which images will be re-

trieved using “flag blue?” Woad blue as the Swedish

or Ukrainian flag or indigo blue as the British or

French?

I suggest results can be disappointing and frus-

trating if the reality of the non-standardization of

colour names is not taken into account.

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Figure 1: The Munsell colour chips with the approximate foci of the English Basic Colour Terms (x).

Figure 2: Stage II language Bété with three BCTs. It is spoken by half a million people in the Ivory Coast.

Figure 4: Stage III

language Karanjá with four BCTs, spoken by about 3000 people in central Brazil.

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