Skip to Content

Color Matching by Phone

Technology from Hewlett-Packard could help shoppers find the right color.
July 11, 2007

Hewlett-Packard (HP) Labs has unveiled a research project that could help people select colors when shopping for products. The technology uses color-correcting and computer-vision algorithms that reside on HP servers. The idea, explains Nina Bhatti, principal scientist at HP Labs, is that consumers use their mobile phones to take pictures of themselves or objects, and then send these pictures to HP servers. Within seconds, the consumer receives a text message with a color recommendation for matching makeup to skin tone, or for finding the right paint hue for the home.

Blending in: A woman (above) holds a color-reference chart while her picture is taken with a cell phone. The picture is sent to HP servers, where the chart helps determine the color of the woman’s skin irrespective of lighting and camera quality. Software in the server matches her skin tone to one stored in a database and recommends the appropriate makeup color via text message.

The research prototype that Bhatti and her team developed is specifically designed to help people find the best shade of makeup based on their skin tone. Not all women who buy makeup purchase it from a cosmetics counter, where an expert can identify the best shade of foundation for them, Bhatti explains. Many buy cosmetics from drugstores, catalogues, and, increasingly, the Web, where there’s no opportunity to test how the color blends with the skin. “Studies have shown that up to 75 percent of women are wearing the wrong shade of makeup,” Bhatti says.

Using HP’s prototype, a consumer simply takes a picture of herself while holding a color-reference chart that could be provided at the makeup counter at stores, in catalogues, or in magazines. When the picture is uploaded to HP servers, software compares the values of the color-reference chart in the picture with the accepted values for these colors. The color-correction algorithm takes the difference between these values and applies it to all the pixels in the picture to eliminate the effects of harsh lighting or poor camera quality.

Once the color in the picture is corrected, face-detection software finds the person’s face and pulls out its predominant color, overlooking blemishes and other irregularities. This corrected face color is then compared with a database of faces, explains Bhatti. HP researchers have a database of 260 women with different skin tones on whom makeup artists have tested products. The consumer receives a text message identifying the makeup color that looks best on the woman in the database with the most similar skin tone. The technology is described in detail in an upcoming issue of the International Journal of Imaging Systems and Technology. Of course, in the real world, cosmetics companies might want to provide the database of faces, using their own makeup artists to determine the matching hue, says Bhatti.

Color-matching algorithms have been used for years to maintain the color of images across devices such as cameras, computer monitors, and printers. And the idea of using color-matching algorithms to help people shop isn’t entirely new, says Joshua Weisberg , director of digital imaging business development at Microsoft, who worked on the color-management system in Vista. Roughly nine years ago, Weisberg helped test a system that corrected the color of clothes from an online catalogue so that there was less difference between the actual color and that on the monitor. But the technology didn’t take off: people had to hold up a color card to their monitor and click a few buttons to calibrate it. “We knew that it did increase the color accuracy of what would be on the monitors,” Weisberg says, “but in reality, most people didn’t want to spend the three minutes to do it.” While it’s too early to tell what impact HP’s effort will have on the market, he says, “it’s great that HP is investing in technology to solve color management problems. ”

Bhatti says that consumers will find the color-matching technology useful in a variety of ways. A person could use the approach to find a sweater that best complements his or her skin tone, for instance. People could also take pictures of paint on their walls and compare the color to paint chips at a hardware store. Additionally, the technology could be modified for comparing the colors of furniture and rugs. But there are challenges here, Bhatti admits: fabrics and hair are prone to a phenomenon in which two colors may appear identical under one light, but not under another.

Bhatti says that HP doesn’t have a timeline for bringing its color-correction product to market. She says that the company is currently “in talks” with cosmetics manufacturers, but it’s not ready to announce partnerships.

Keep Reading

Most Popular

DeepMind’s cofounder: Generative AI is just a phase. What’s next is interactive AI.

“This is a profound moment in the history of technology,” says Mustafa Suleyman.

What to know about this autumn’s covid vaccines

New variants will pose a challenge, but early signs suggest the shots will still boost antibody responses.

Human-plus-AI solutions mitigate security threats

With the right human oversight, emerging technologies like artificial intelligence can help keep business and customer data secure

Next slide, please: A brief history of the corporate presentation

From million-dollar slide shows to Steve Jobs’s introduction of the iPhone, a bit of show business never hurt plain old business.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at with a list of newsletters you’d like to receive.