Biometric facial Image autocapture, quality assurance, and camera abstraction

PreFace is an SDK that automatically captures and analyzes biometric facial images in order to maximize their quality and matchability. It can enable a biometric enrollment application to automate the facial image capture process and also ensure that enrolled images comply with ISO standards or backend processing system and are of sufficient quality to perform biometric matching.

PreFace integrates with the camera to perform analysis of the live facial image stream or video. Once basic quality criteria are met, PreFace triggers the camera to take a full-resolution image. Following capture, PreFace performs a thorough image analysis, which reports image geometry, non-compliant features, and spoof attempts. Scaling, rotation, and cropping of the image is performed to meet highly configurable targets and thresholds. These thresholds are derived from the ISO/IEC 19794-5 standard for biometric facial image quality. Results are reported to the user. PreFace also includes a robust face finder, able to locate multiple faces in a single frame in both still shots and video.

PreFace Screenshot

PreFace Screenshot

Learn about PreFace Mobile

Features and Functionality

  • Automates photo capture and improves operational efficiency of the capture process
  • Maximizes the visual quality of biometric facial images for human comparison
  • Improves matching performance by screening non-compliant images upon capture
  • Performs automatic “rotate, scale, crop” geometrical corrections
  • Notifies operator of pre- and post-correction non-compliant features
  • Creates compliant ISO/IEC 19794-5 biometric records
  • Ensures compliance with ANSI/INCITS 385-2004 and ISO/IEC 19794-5 standards for biometric facial image quality
  • Integrates market leading digital cameras, web cams, and industrial cameras, including new cameras as they arrive on the market
  • Performs estimation of demographic qualities; age, race, and sex
  • Estimates pose: yaw, pitch, and roll
  • Detects and analyzes multiple faces in an image
  • Optimizes brightness and contrast to compliance (includes a screen shot of before and after)
  • Identifies key facial feature coordinates including eyes, nose, mouth and chin
  • Compresses image to targeted file size or quality level
  • Supports multiple image formats: PNG, BMP, TIF, JPEG, JPEG 2000, RAW-8, RAW-24

SDK Features

  • Fully featured C Language API
  • C#/.NET wrappers
  • Example programs with source
  • Java Native Interface support
  • Android and iOS support (PreFace Mobile)

Camera API

PreFace includes “Camera API,” which serves to abstract camera hardware and integrate software-driven autocapture with a variety of consumer-grade digital cameras, webcams, and industrial cameras. It is designed to greatly simplify the task of integrating a facial image camera into a photo capture application.  Camera API provides a method by which to support many different cameras within a single application: program once, and use with many camera models. Support for new cameras is added in subsequent revisions of the SDK as they become available. Camera API enables a biometric application to operate equivalently with a variety of devices over time or within the same system. Cameras are also tested and submitted for approval by the GSA for use in FIPS 201 compliant “PIV” U.S. government employee credentialing systems. An up-to-date list of cameras supported by Camera API is available from Aware upon request.


  • Facial recognition
  • Face finding
  • Automated Biometric Identification Systems (ABIS)
  • Biometric authentication
  • Fraud prevention
  • Citizen ID and voting systems

PreFace functionality includes:

  • Pose Angle Yaw
  • Dynamic Range
  • Brightness
  • Saturation
  • Smile
  • Eye Contrast
  • Eye Obstructed (Left or Right)
    – Glasses Frames
    – Hair
    – Closed Eye
    – Eye Valid
  • Off-angle Gaze
  • Red-eye
  • Number of Image Channels
  • Background
    – Gray
    – Uniformity
    – Clutter
    – Type
    – Color Balance
    – Pad Type
  • Conditional Padding
  • Illumination Asymmetry
  • Facial Shadows
  • Focus
  • Sharpness
  • Unnatural Skin Color
  • Glasses
  • Glasses with Dark Lenses
  • Glasses Glare
  • Glasses with Heavy Frames
  • Forehead Obstructed
  • Image Width
  • Image Height
  • Eye Separation
  • Eye Axis Location Ratio
  • Centerline Location Ratio
  • Image Height/Width Ratio
  • Image Width/Head Width Ratio
  • Head Height/Image Height Ratio
  • Eye Axis Angle
  • Estimated Age
  • Gender-Female
  • Gender-Male
  • Race-White
  • Race-Black
  • Race-Asian
  • JPEG Quality Level
  • File Size
  • JPEG2000 Compression Ratio
    – Within ROI
    – Outside ROI
  • Image Format