The U.S. Intelligence Advanced Research Projects Activity's (IARPA) newest contest challenges participants to build an automated fingerprint collection system that matches the performance of human operators.
The current nail-to-nail (N2N) fingerprint approach requires a trained operator to hold and physically roll the subject's finger over a surface to capture the complete print. The "slap" fingerprint utilizes a single press method that does not require an operator, but the system only captures the parts of the finger touching the sensor.
The N2N Fingerprint Challenge offers $325,000 in prizes for devices that can capture the entire fingerprint. Collected data will be compared against N2N and latent data using conventional fingerprint-recognition algorithms, and participants will be judged based on traditional biometric performance measures and the speed of the collection process.
The challenge will run in two stages through the fall of this year, ending in a live test in which finalists will demonstrate their devices.
The contest is the latest in a series of competitions backed by the U.S. government to spur innovation in the private and philanthropic sectors. Automatic Speech Recognition in Reverberant Environments Challenge, an earlier IARPA contest, asked teams to build speech-recognition systems that can accurately transcribe speech recorded in noisy and reverberant conditions.
From Network World
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