Privacy-preserving license plate image processing

Abstract

Advances in license plate detection and recognition software severely threaten privacy. Intended originally for video surveillance such as the law enforcement at automatic toll booths, license plate recognition software becomes so powerful that it can identify license plates from low-resolution and blurred images illegible to the human eye. However, the technology can be adversely used to track individuals regardless of suspicion, violating privacy, through ever present webcams, in Traveler Information Systems, for instance. This paper introduces a novel engineering solution to privacy-preserving license plate recognition. A trivial solution to protect the privacy of individuals in video surveillance data is to black out each license plate; it effectively thwarts license plate recognition but renders no practical use as all information being obscured. The new system presented in this paper enables privacy preservation in the images containing license plates as well as car features while allows identification of particular license plates with legitimacy similar to a specific search warrant. Such dual purposes are fulfilled with an orchestra of information technologies. Pseudo-anonymity, a disguised identity held by many individuals, preserves privacy by ensuring the failure of license plate recognition. Steganography, security through obscurity or information hiding, reveals the license plate of a suspect by a protocol of synchronized pseudo random number generation. The synchronization protocol is superior over both symmetric encryption problematic with key distribution and asymmetric schemes involving expensive computation. Experiments are conducted on a real world Traveler Information System with favorable results.