How Facial Recognition Systems Work

A newly-emerging trend in facial recognition software uses a 3D model, which claims to provide more accuracy. Capturing a real-time 3D image of a person's facial surface, 3D facial recognition uses distinctive features of the face -- where rigid tissue and bone is most apparent, such as the curves of the eye socket, nose and chin -- to identify the subject. These areas are all unique and don't change over time.

Using depth and an axis of measurement that is not affected by lighting, 3D facial recognition can even be used in darkness and has the ability to recognize a subject at different view angles with the potential to recognize up to 90 degrees (a face in profile).

Using the 3D software, the system goes through a series of steps to verify the identity of an individual.

Detection

Acquiring an image can be accomplished by digitally scanning an existing photograph (2D) or by using a video image to acquire a live picture of a subject (3D).

Alignment

Once it detects a face, the system determines the head's position, size and pose. As stated earlier, the subject has the potential to be recognized up to 90 degrees, while with 2D, the head must be turned at least 35 degrees toward the camera.

Measurement

The system then measures the curves of the face on a sub-millimeter (or microwave) scale and creates a template.

Representation

The system translates the template into a unique code. This coding gives each template a set of numbers to represent the features on a subject's face.

Matching

If the image is 3D and the database contains 3D images, then matching will take place without any changes being made to the image. However, there is a challenge currently facing databases that are still in 2D images. 3D provides a live, moving variable subject being compared to a flat, stable image. New technology is addressing this challenge. When a 3D image is taken, different points (usually three) are identified. For example, the outside of the eye, the inside of the eye and the tip of the nose will be pulled out and measured. Once those measurements are in place, an algorithm (a step-by-step procedure) will be applied to the image to convert it to a 2D image. After conversion, the software will then compare the image with the 2D images in the database to find a potential match.

Verification or Identification

In verification, an image is matched to only one image in the database (1:1). For example, an image taken of a subject may be matched to an image in the Department of Motor Vehicles database to verify the subject is who he says he is. If identification is the goal, then the image is compared to all images in the database resulting in a score for each potential match (1:N). In this instance, you may take an image and compare it to a database of mug shots to identify who the subject is.

 

Facial Recognition Systems Uses

 

In the past, the primary users of facial recognition software have been law enforcement agencies, who used the system to capture random faces in crowds. Some government agencies have also been using the systems for security and to eliminate voter fraud. The U.S. government has recently begun a program called US-VISIT (United States Visitor and Immigrant Status Indicator Technology), aimed at foreign travelers gaining entry to the United States. When a foreign traveler receives his visa, he will submit fingerprints and have his photograph taken. The fingerprints and photograph are checked against a database of known criminals and suspected terrorists. When the traveler arrives in the United States at the port of entry, those same fingerprints and photographs will be used to verify that the person who received the visa is the same person attempting to gain entry.

However, there are now many more situations where the software is becoming popular. As the systems become less expensive, making their use more widespread. They are now compatible with cameras and computers that are already in use by banks and airports. The TSA is currently working on and testing out its Registered Traveler program. The program will provide speedy security screening for passengers who volunteer information and complete a security threat assessment. At the airport there will be specific lines for the Registered Traveler to go through that will move more quickly, verifying the traveler by their facial features.

Other potential applications include ATM and check-cashing security. The software is able to quickly verify a customer's face. After a customer consents, the ATM or check-cashing kiosk captures a digital image of him. The FaceIt software then generates a faceprint of the photograph to protect customers against identity theft and fraudulent transactions. By using the facial recognition software, there's no need for a picture ID, bankcard or personal identification number (PIN) to verify a customer's identity. This way businesses can prevent fraud from occurring.

While all the examples above work with the permission of the individual, not all systems are used with your knowledge. In the first section we mentioned that systems were used during the Super Bowl by the Tampa Police, and in Ybor City. These systems were taking pictures of all visitors without their knowledge or their permission. Opponents of the systems note that while they do provide security in some instances, it is not enough to override a sense of liberty and freedom. Many feel that privacy infringement is too great with the use of these systems, but their concerns don't end there. They also point out the risk involved with identity theft. Even facial recognition corporations admit that the more use the technology gets, the higher the likelihood of identity theft or fraud.

As with many developing technologies, the incredible potential of facial recognition comes with some drawbacks, but manufacturers are striving to enhance the usability and accuracy of the systems.

 

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