Single Image Liveness Detection

Single Image Liveness Detection

Single Image Liveness Detection

Get the most friction-less liveness detection experience using a single image.

What is Single Image Liveness Detection?

Single Image Liveness is a biometric security mechanism that uses machine learning algorithms to verify whether a captured image was taken on the spot from the live person, or is a spoof (such as a photograph, video, or mask).

This allows for much less user-friction compared to other forms of liveness, increasing the pass rate of genuine customers.

Liveness Detection

The Single Image Liveness Detection Process

The system captures a single image from the user, then analyzes multiple metrics,
including but not limited to:

scan

Edge Detection

Images printed on paper can have sharp transitions or changes in pixel intensity, which can be detected.

Color Spectrum Analysis

Non-real faces can have color inaccuracies, limited ranges, or unnatural hues due to different limitations.

Light Pattern Analysis

Images captured form a screen can produce reflections and/or glares, detectable through light pattern analysis.

Why Use Single Image Liveness?

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Higher Pass Rates

Highly reduced user friction means a much lower user drop-off rate, leading to more customers.

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Cost Effective

Eliminating the cost of processing video footage and other overheads means lower overall costs.

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More Revenue

As you get more customers for your business, that means that a lot more potential revenue.

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Frequently Asked Questions

What is Single-Image Liveness Detection?

Single-image liveness detection is a biometric technique that utilizes a single retained image to check if the person is real or fake. However, it examines the visual sample to distinguish the real faces from spoofed attacks.

How Does Single-Image Liveness Detection Work?

It depends on the artificial intelligence algorithms to check image aspects, for instance, texture, lighting, alongside facial symmetry. Also, these features assist in recognizing the irregularities in spoofed images or deepfakes.

Can Single-Image Liveness Detection Handle Deepfake Attacks?

Definitely, latest single-image liveness detection can disclose the irregularities in deepfake-generated photos. It highlights slight changes or mismatches that don't appear in the live image.

What Types of Spoof Attacks Can It Prevent?

Spoof attacks with digital screens, 2D masks, and printed photos can be avoided with single image liveness detection. It distinguishes between real and fake faces by detecting texture, lighting, and depth cues.

What are the Accuracy Rates of Facia's Single-Image Liveness Detection?

With just one selfie, Facia's single-image liveness detection can distinguish real users from spoof attacks with up to 98.8% accuracy. Without requiring user movement, it successfully recognizes printed images, 2D/3D masks, and screen replays.