Category Archives: advanced stuff

Colour Design Strategies

advanced stuff,

I have been in the School of Design at the University of Leeds for over 21 years. Before that I worked in colour engineering. Before that in colour neuroscience. My first degree was in colour chemistry. So I have had a varied career but colour has been at the heart of it. I don’t think I thought too much about design as a discipline before joining Leeds. But your environment influences you, of course. Most of mu PhF students at Leeds have been design students. And I have taught on many undergraduate and postgraduate design programmes. So I picked up a few things along the way.

In the video below I run through some of the key concepts I have picked up around colour design, especially in the context of packaging and product design.

In this video I mention some work by my doctoral student Luewn Yu which I would like to expand upon a little here.

This is the paper

In this paper we showed people lots of products in lots of different colours and we asked which one they would prefer to buy. We also, at the end, asked what was their favourite colour. For each product we also asked to what extent did they think the product colour was functional.

What do we mean by functional? Well, it’s where the colour is more than decorative. Where, for example, in some products the colour might denote how strong a solution is or where it might suggest that a product smells or tastes this or that way.

Take the products below:

We might expect the middle on to smell of lemons for example. And maybe the right-hand one to smell of apples (though in this case it is neutral or original). And take the product below:

If it was darker green we might expect it to be stronger.

So for each product we have a measure of how likely the consumer is to choose the product in their preferred general colour (we call this product colour consistency rate) and we also have a measure of how functional the colour is (we call this colour performance/functionality). Our hypothesis was that people would choose a product in their favourite colour if there was no performance of functional implication of the colour. On the other hand, we thought that people would be less likely to choose a colour in their general preferred colour if colour is somehow important or has some other implication.

And that is what we and what the graph of our results below shows.

So all the blue dots represent different products. On the right you have products where the colour signifies something (such as washing up liquid or mouth wash) and on the left we have products where there is no meaning to the colour (such as a corkscrew or a pair of scissors).

As expected, for products on the left the product colour consistency rare is high; that is people tend to choose these products in their general favourite colour if given the choice. On the other hand, for products on the right the product colour consistency rare is low; that is, there is no consistency between the colour of the product that they pick and their general preferred colour. This allows us to predict quite well whether it makes sense for a product to be offered in lots of different colours or not.

The most important thing about colour

advanced stuff, , ,

I have worked in colour pretty much all my life. In 1980 I started learning at the University of Leeds where I was enrolled on BSc Colour Chemistry. That was 44 years ago!

Since 1980 I have been learning, working, researching and teaching colour for almost all of those years. I have learned a lot and I am sure I still have a lot to learn. For example, only a few weeks ago learned that the colour name magenta is named after an actual town in North Italy. I discovered this when doing some research about colour names for the following video.

And I recently I have been learning so many new things from a book called The History of Colour by Neil Parkinson. I can’t tell you how much I am enjoying reading it. But more about that later.

I often say to people that the most important thing about colour that I ever learned is called the principle of univariance. I read about it in Brian Wandell’s book Foundations of Vision in the 1990s. It was discovered by someone called William Rushton in the 1960s. It is about how the human cones operate and it is so fundamental to explaining how colour vision works. It explains how we can discriminate between different wavelengths of light despite only have three types of light-sensitive cells that each have broad-band spectral sensitivity.

It explains why we have metamerism – which is where, for example, two spectrally dissimilar objects can look the same colour when viewed under one light source but then be a mismatch when viewed under a different light source.

It explains why additive mixing occurs. Why we can additively mix red and green light to get yellow. And it even explains subtractive colour mixing if you think deeply about it.

So the video How does colour vision work?, is really about how cones work and the principles of univariance.

Why are things coloured?

advanced stuff, , ,

Things are coloured because we have visual systems. In other words, without us – or some similar sentient being – there would be no colour.

“By convention there is sweetness, by convention bitterness, by convention color, in reality only atoms and the void.”, Democritus, 460-370 BCE.

If we eliminated all living beings from the universe there would be no colour, no sound, no smell. All that would remain would be physical stimuli.

I really believe this. But it doesn’t mean that colour doesn’t exist. It’s like saying that just because they are things that we experience – things that our brains produce – then pain and love don’t exist. Of course pain and love exist. But they don’t exist in the absence of sentient beings and the same can be said for colour. And all of our perceptions of course.

But this video – below – is not about that. It is about how everyday objects such as paints, plastics, textiles, prints etc. interact with light. Why do some objects absorb short wavelengths and others absorb long wavelengths.

For most objects it is all about dyes and pigments. Please watch the video below to hear more about this. And don’t forget to click like if it was worth your time.

Colour Matching and Cones

advanced stuff, knowledge, technology, , ,

Earlier today I posted something on quora about who many colours there are. It’s quite a long post. You can read it here. However, if you want the short cut the answer is 3-5 million. 🙂

However, I also linked to the post on LinkedIn and someone asked me a question about the relationship between colour-matching functions and cone sensitivities so I thought I would make a new post today about that topic. I have used my message on LinkedIn as the basis for this post but modified it a little to make it suitable for general consumption.

Here are two diagrams:

This shows the actual spectral sensitivities of the MLS cones in the human eye

The 1931 CIE XYZ colour-matching functions

It’s another common misconception that people get these two diagrams confused. The cone spectral sensitivities are the actual sensitivities of the cones in the eye. Although people often say that the eye responds mainly to red, green and blue light, it’s not so simple.  In 1931 the CIE measured the colour matching functions. One of the reasons that they did this was that in 1931 we didn’t actually know what the cone spectral sensitivities were; these were only known for sure in 1964. So in 1931 the CIE measured the amounts of three primary lights that an observer would mix together (additively) in order to match a single wavelength of light. And they did this for each wavelength. The second of the diagrams above shows the amounts of each of the primaries needed to match each wavelength on the spectrum.  Originally, the CIE used three lights (these were RGB)  or primaries. However, they mathematically transformed their RGB colour matching functions to create the XYZ colour matching functions. These are sometimes also known as the CIE colour matching functions or the CIE standard observer.

These are the original CIE RGB colour-matching functions

The point of these (XYZ) colour matching functions are that they allow us to calculate the CIE tristimulus values XYZ of an object if we know the spectral reflectance of the object and the light it is viewed in. The XYZ values are the amounts of the three XYZ primaries that an observer would, on average, use to match that object viewed in that light source. If two samples have the same XYZ values then they are a visual match; because an observer would, on average, use the same amounts of the XYZ primaries to match each. And this was the whole point of the CIE system; to determine when two colour stimuli are a visual match.  Had we known the cone spectral sensitivities in 1931 it’s possible that history would have taken a different course and that instead of having CIE XYZ we would simply calculate the cone responses LMS. And we could say that if two samples have the same cone responses they are a visual match. But I guess we’ll never know.

Now, if two samples have the same XYZ values then they will have the same cone responses. This is a bit technical but this is true because the cone spectral sensitivities are a linear transform of the CIE XYZ colour matching functions. They are also a linear transform of the CIE RGB colour-matching functions.

The colour-matching functions depend upon which primaries are used whereas the cone spectral sensitivities are more fundamental. Doesn’t this make the colour-matching functions arbitrary? Not really. Although the actual shapes of the colour-matching functions depend upon the actual primaries used, the matching condition does not. If two samples generate the same cone responses then the observer would match them with the same amounts of the XYZ primaries and the same amounts of the RGB primaries.

On this page – https://en.wikipedia.org/wiki/CIE_1931_color_space – you can see the cone spectral sensitivities and the RGB and XYZ colour matching functions.

Quora is alive and kicking

advanced stuff, knowledge, opinions/rants,

I have been posting here on Colourchat for a long time. I think it is nearly 10 years but it could be longer. Time flies. However, I just wanted to let you know that I also post on a website called quora. Quora is a site where people post questions and other people can answer them. It used to be completely free although quora have recently introduced a model where people can put their answers behind a pay wall. However, my answers are free and I just wanted to let you know that there is a lot of stuff there that might interest you. I have only been posting there about 3 years but my answers have received over 2 million views (whereas Colourchat has had less then 500,000 views over a much longer time period).

However, quora is a little bit tongue-in-cheek. Not all of the answers are serious though most of mine are. I still reserve my best content for Colourchat where I can give a lot more detail. And I also have a patreon page where I do charge a small fee (because that’s how patreon works) where I am curating my most detailed content and this includes quite a few videos that are unique to the patreon site.

Anyway, if you want to have a look at quora you could take a look at this post I made today which answered the question of why a mixture of red and blue light doesn’t generate a hue that is between the two ends of the spectrum. I hope you like my answer. What I focus on – and what I am striving towards though perhaps not always achieving – is to try to answer these questions in a way that is maximally informative but at the same time doesn’t require an understanding of maths, for example, so that it is maximally inclusive.

Analysing CIELAB values

advanced stuff,

Imagine you have a standard (std) and a batch (btx) and you have the CIELAB values of each. How can you analyse these numbers, in particular, the differences? This post explains how to do it.

Let’s start with a real example.

Now what can we say about these two samples. Well, we can calculate the colour difference. If we want to calculate the CIELAB colour difference we can simply calculate the differences in each of the three dimensions, square them, add them and take the square root. Thus DL* = 2, Da* = 10, and Db* = 6. So the CIELAB colour difference is sqrt(4 + 100 + 36) = sqrt(140) = 11.8. This is quite large. Of course, we might prefer to use some other measure of colour difference such as CMC or CIEDE2000. But let’s stick with CIELAB.

The next thing is to look at the individual differences. Since a* is redness we might conclude that the btx is redder than the std (the btx has an a* of 36 whereas for the standard it is only 26). And since b* is yellowness we might conclude that the btx is yellower than the std (the btx has a b* of 9 whereas for the standard it is only 3). However, it is really confusing to look at the data this way. Perceptually, we might be interested in whether there is a chroma difference (is the batch weaker or stronger?) and whether there is a hue difference. Let’s plot these samples in the a*-b* plane of CIELAB.

As you can see, the btx has a larger a* value and a larger b* value than the std. However, we cannot deduce anything about hue or hue differences just by looking at a* or b* on their own. Hue is an angular term in CIELAB space.

As you can see from the above figure, the hue of the standard is 6.6 degrees and the hue of the btx is 14.0 degrees. The CIE method to calculate hue descriptors is to move radially from one sample to another and note which axes we cross. So if we start of with the btx we move clockwise towards the std; we keep going and we cross the red axis and then (if we keep going) we cross the blue axis. So we would conclude that the std is redder (bluer) than the btx. According to CIE guidelines, one of these descriptors makes sense and the other doesn’t.

In this case, I would say that the std is bluer than the btx. In hue terms it doesn’t really make sense to say that the std is redder than the btx when they look quite red anyway. And we would say that the btx is yellower (greener) than the std.

In terms of chroma we calculate the distance from the centre for each of the colours. As you can see from the diagrams, the batch is much further out from the centre than the std.

So, in conclusion, we would say that the btx is lighter, stronger and yellower than the std. The std is darker, weaker and bluer than the btx.

The point of this is to highlight that we cannot make decisions about hue and chroma by looking at just a* and b*. We need to look at both a* and b*. Better than trying to do this is to calculate the polar coordinates, hue and chroma. These are generally more helpful than the cartesian coordinates, a* and b*. In my experience, people have a reluctance to think in terms of polar coordinates and I think this is because they have much greater experience at school with cartesian coordinates. Everyone spends their schooldays looking at certesian plots of x vs. y don’t they? But getting to grips with polar coordinates in colour science will really pay off in the long run.

Notice that just because the batch has a larger a* value than the std, this does not make the batch redder. In fact, as can be seen from the first diagram, it is the std that is closer to the a* (red) axis than the btx, despite having a smaller a* value.

What type of colour information do designers want?

advanced stuff, , , ,

In this study we were interested in which type of colour information designers want. We carried out surveys and interviews (with senior designers and brand managers) and the results are summarised below:

We used a card-sorting technique in our interviews to ensure that the participants knew what each of our terms meant.

We found that colour meaning was one of the aspects of colour that designers would like to be able to put their finger on; it was more important that colour trend information in fact! We also looked some existing colour tools and found that none of them really offered the most important information that designers and brand managers want to know about colour. What would be really cool would be a tool that provided accurate information about the meanings that colours have in different cultures and perhaps in different contexts.

The full paper will shortly be published in Color Research and Application.

Won S & Westland S, 2018. Requirements capture for colour information for design professionals, Color Research and Application.

The full publication details will be added here when they are available. Meanwhile, you can read it here.

 

Digitizing Traditional Cultural Designs

advanced stuff, culture, design, , ,

A bojagi is a traditional Korean wrapping cloth.

There is currently interest in re-using traditional and cultural designs in modern commercial applications. The bojagi is one of these traditional designs that could be reinvented and hence reinvigorated. But how can a designer create bojagi patterns for use in new digital design?

Working with Meong Jin Shin I developed a software tool that can create a wide range of different bojagi. We identified 8 different classes of traditional bojagi as shown below:

We then created a software tool that would allow a user to create new bojagi which would have the same visual characteristics as one of these 8 traditional classes.

We had some designers in Korea evaluate the tool and they were quite impressed. Although in this study we worked with Bojagi, in fact we were interested in exploring the general method of using digital tools such as this one to allow users to explore traditional designs and to use them in their contemporary design work. The ideas could be easily extended to cover other traditional designs such as tartan. The software could also be added to a package such as Adobe Photoshop as a plug-in.

You can read the full paper that we published here.

Shin MJ & Westland S, 2017. Digitizing traditional cultural designs, The Design Journal, 20 (5), 639-658.

Does context affect colour meaning?

advanced stuff, design, psychology

One of the reasons that colour is such a powerful and important property is that it conveys information. Colour imparts meaning. If you see a big red button you may understand that something important or dramatic may happen if you press it. If someone is wearing bright yellow clothes it might imply something about their personality. Take a walk into a toy store and notice the swathes of pink in the girls’ section (though note that I don’t imply that this is a good thing; indeed, I would refer you to the pink stinks campaign in order that you may become a right-thinking person). But it is clear that the manufacturers of the toys believe that the colour pink will indicate that these are toys for girls and that its use may even make girls want to have these toys. If you see two washing-up liquids and one is green and one is yellow you might think that they would smell of apples and lemons respectively before you even open them! Colour sells. And part of the reason that colour sells is that it is informative. Colours have meanings.

But does colour per se have meaning or does colour only have meaning when it is an attribute of a product? The colour red on an emergency stop button may have one meaning but the colour red on the soles on Louboutin shows may have an altogether different meaning. And, of course, colours mean one thing in one culture but another in a different culture; black is commonly associated with death in the West but in China and some other countries in Asia death is more commonly associated with white. Nevertheless, I do believe that colour per se, that is colour in an abstract sense, does have meaning and there are a number of studies out there that tend to support me (though some social scientists, in particular, who would disagree).

What I mean by this is that if we take a culture, such as the UK, then a colour such as red will be associated with various ideas and concepts to varying degrees of strength. Red may take on different meanings when applied to different products (that is, in context). But is there any relationship between the abstract colour meaning and the product colour meaning? This is the question that Seahwa Won (who was a PhD student working with me) and I asked each other that led to a piece of work and an academic paper.

If there is no relationship between abstract colour meanings and  product colour meanings then it might mean that there is little practical or commercial value in studying abstract colour preferences (though it may still be worthy of study). On the other hand, if there is a relationship between abstract colour meanings and  product colour meanings then knowing the former may help us to predict the latter in a wide range of circumstances. To carry out our study we used scaling (I have blogged about some aspects of scaling before) where we try to quantify the perceptual response of participants to physical stimuli. For example, we show people a colour patch on a display screen and then below this there is a slider bar which allows the participants to respond whether the colour is warm, for example, or cool. We do this for lots of colours and lots of participants (nobody said colour science was easy!!) and then we can average these and have a warm-cool scale along which we can place all the colours. When we do this, for example, we find that participants think red is much warmer than blue. However, what Seahwa and I also did was to repeat this type of experiment with different colour products rather than simple colour patches. Would participants place a red toilet roll on the same point on the warm-cool scale as the red colour in an abstract sense? If they would then we can conclude that abstract colour preferences and product colour preferences are related.

We did this for quite a few different scales (warm-cool, expensive-inexpensive, modern-traditional, etc.) and for for a few different colours. The figure below shows the results when we explored the masculine-feminine scale. Look at the left-hand part first, where it says chip along the bottom. Chip indicates the abstract colour meanings (for example, when participants view a simple square or chip of colour). Note that participants scale beige, red and yellow as being feminine colours whereas black, blue and green are more masculine colours. Now look at the right-hand part of the figure, where it says crisps (in the UK a crisp is something you buy in a bag to eat; Americans may call these potato chips). When we showed crisp packets that were differently coloured the masculine-feminine scale values were almost the same as for the abstract colours themselves. We found strong relationships between abstract colour meanings and product colour meanings more often than not.

Our findings are broadly compatible with an earlier study by Taft in 1996 who found that there was no significant effect of context on colour meaning in the majority of cases. We did find some effects of context though. For example, black-coloured medicine was perceived as being more feminine that the abstract colour black itself.

We published this paper in 2016 in the journal Color Research and Application and you can read the paper in full here.

Won S & Westland S, 2017. Colour meaning in context, Color Research and Application, 42 (4). 450-459.

Consumer Colour Preferences

advanced stuff, design, psychology, ,

How does your personal colour preference affect the colour of the things that you buy?
It is well known that people prefer some colours more than others. Personally, I much prefer red to blue. But I am probably in a minority. Many studies have shown that blue is the most popular hue with yellow being one of the least popular hues. But this is when we think of colour in an abstract sense. But what about when colour is applied to a product: a pair of trousers, a toothbrush, a fidget spinner? Well, my favourite colour is red but I have never owned a pair of red trousers. I tend to buy buy blue or brown trousers even though I don’t really like the colour blue in the abstract sense. But are there products where, if we were presented with a choice in colour, we would tend to buy the colour product that matches our abstract colour preference? This is the question that I set out to answer answer two years ago with my colleague Meong Jin Shin. We carried out an experiment over the internet where we presented people with a choice of products in different colours and asked which they would buy given the choice. They were presented with images a little like the one below:

After we asked participants which product they would buy for a number of different products we then asked them what their favourite colour was in an abstract sense (we showed a number of colour patches on the screen and asked the to click on the one they liked best). Our hypothesis was that for some products participants would tend to select products that closely matched their most preferred abstract colours but that for some other products we would not find this.

This is exactly what we found. For some products, such as bodywash, we found that people tended to prefer a particular colour for the product (in this case, blue). The figure below shows the results for bodywash. The rows represent the colour of the products and the size of the circle in each row represents the proportion of people who generally preferred either red, orange, yellow, green, blue or purple that selected that product colour. As you can see below the majority of people chose a blue bodywash no matter what their abstract colour preference was.

However, for the toothbrush product a very different picture emerged. As shown below, people who liked red generally tended to select a red toothbrush and people who preferred purple tended to select a purple toothbrush. For example, 41% of people who preferred green selected a green toothbrush.


So sometimes people’s personal colour preference could be used to predict which colour product they would choose to buy given the choice (and sometimes it couldn’t be). How could this be useful? Well, if we could predict which products where this is true then it would suggest that a multi-colour marketing strategy could be appropriate. Also, imagine you are in a supermarket and you are presented with an offer – 50% off toothbrushes today – and alongside this you see a red toothbrush. If red was your favourite colour then there might just be a little more chance you would accept the proposition. If a supermarket could predict a consumer’s personal colour preference …. [more of this in a later post].

This paper was published in 2015 in the Journal of the International Colour Association. You can read the full paper for free here.

Westland S & Shin M-J, 2015. The Relationship between Consumer Colour Preferences and Product-Colour Choices, Journal of the International Colour Association, 14, 47-56.