Face Recognition Enters a New Dimension

Face Recognition Enters a New Dimension
Three-dimensional face readers are ideal for identity management and access control. Matthew Bogart, Vice President of Marketing for Bioscrypt, discusses how they overcome previous failings.

Three-dimensional (3-D) face recognition solutions add another dimension to face recognition technology and in so doing, transform it. Long hampered by a reputation for inaccuracy and unreliability, face recognition technology was considered the poor cousin of the far more mature fingerprint biometric technology. However, advances in real-time 3-D imaging have addressed those historic concerns and turned 3-D face recognition into a compelling biometric technology ideal for access control. 3-D face recognition is now fast, accurate and simple. They can make matches in under a second with precision.

Face recognition has been gaining popularity as a biometric identity verification solution with revenue expected to exceed US$1 billion annually by 2012, according to an International Biometric Group (IBG) report, Biometric Market and Industry Report 2007-2012.

3-D face recognition systems are being used by financial institutions, Fortune 500 companies, biopharmaceuticals, casinos and organizations in the transportation sector to enhance security without introducing complex access control procedures that make it difficult for employees to gain entry. In organizations with a large workforce, speedy access control is a must and with 3-D face recognition, companies can quickly authenticate thousands of employees as they begin a shift.

Advantages of 3-D

While 2-D face recognition is being used by law enforcement for identification, it is not significantly deployed for verification systems. Identification involves comparing an existing image against a large image database in order to identify the individual depicted. In verification solutions, a biometric identifier is compared either to another template called up through a PIN number or smart card or against a small database of other templates.

However, because 2-D face recognition systems are affected by lighting conditions and the pose of the individual's face, they are not ideal for access control. In U.K. trials for biometric passports, for example, only 69 percent of able-bodied volunteers and 48 percent of disabled participants were correctly authenticated. Some 3-D facial recognition systems, however, use their own near-infrared light source, which means they can make accurate matches even in poor lighting conditions.

3-D facial recognition technology also has other advantages. It is possible to collect more data points with 3-D, and the types of data points collected are more valuable. While a 2-D system might make a match using such data points as the distance between the eyes, 3-D uses data such as the curvature of the forehead. The latter is more useful because it allows 3-D systems to make matches, even if a face changes as a result of a scar or other visual features.

How 3-D Works

There are two main approaches to 3-D facial recognition: the stereo approach and the structured light approach. Stereo 3-D systems create 3-D images by synthesizing two or more 2-D photos. This computingintensive (and thus, expensive) approach adds an unnecessary layer of complexity to 3-D face matching and, like 2-D, is hampered by poor lighting conditions.

Structured light 3-D face readers, on the other hand, shine an invisible near-infrared, grid-shaped light on a user's face and a camera takes a picture of the distortions in the grid caused by the face, collecting approximately 40,000 data points. Because structured light 3-D face scanners use their own light source, they can work in poor lighting conditions.

They can also accommodate various facial positions, making it easier for users to confirm their identity as they pause in front of the face reader to verify their identity.

3-D face readers simplify data entry for end users who can confirm their identity using only their face to prove they are who they say they are. Users just walk up to the reader and pause while the reader either searches the database for a face that matches or checks the face against a template called up by a proximity card, smart card or token, making a match in under a second.

The enrollment process is likewise simple  taking just a few minutes. Again, the enrollment reader projects a near infrared light pattern on the user's face. The light pattern is modified by the surface geometry of the face and the camera precisely records the pattern distortions caused by the face. This modified pattern is input into a 3-D reconstruction algorithm in order to create a 3-D mesh image of the face using triangulation. The face geometry can be measured in millimeters. However, the reconstructed image is not stored in the database. Instead, a biometric template is extracted from the 3-D facial geometry and the numeric template is stored in the database. A matching algorithm then checks the face presented at the entry point to restricted areas against the template already stored.

Security Thresholds

With any biometric implementation, organizations have the ability to set different thresholds for security. At a high threshold which raises the number of data points that must match in order for someone to be granted entrance, there will be fewer false accepts  the authorization of unauthorized personnel  but also an increase in false rejects  denying access to someone who is actually authorized. At lower thresholds, the number of false accepts increases while the number of false rejects decreases. Companies are free to assess the levels that are appropriate for their security requirements. At very high thresholds, they can be sure to keep intruders out, but some employees may have to be more exact in how they present themselves for verification. At low thresholds, authorized employees can easily gain entrance, but someone without authorization might also be permitted through.

With 3-D face recognition, organizations, such as financial institutions and airports, that cannot tolerate any false accepts can set high security thresholds without a significant increase in the number of false rejects. This means their employees can get into the areas they need access to while unauthorized personnel are kept out.

Like other biometric solutions, 3-D face recognition uses who a person is, rather than what they know or what they have for identity verification, significantly increasing security without sacrificing convenience. Passwords and PIN numbers  what a person knows  can be stolen, forgotten, lost or lent out. Smart cards, proximity cards and tokens  what a person has  can likewise be stolen, misplaced, forgotten, forged or borrowed. A person's face or fingerprint  what a person is  however, is always with them and can not be stolen or copied. Using face recognition alone or in conjunction with another authentication factor for dual- or multifactor authentication, therefore, significantly increases security.
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