registration plate reading of vehicles
12 3 1. Reflections and distortions in night conditions. 2. The technology’s ability to capture clear images in these conditions. 3. Reading a car's number plate at the gate.
Getting a good image under those conditions requires an optimised camera designed for this process and with a specialised and optimised illuminator.
Fortunately, that technology has been successfully developed and is currently deployed in use at hundreds of sites worldwide. It can show driver and passenger faces through the heaviest of tinted windows and is not affected by many differing weather conditions up to distances of 15 metres.
Capturing the Registration Plate for added security combination (2-factor detection)
Two-factor authentication increases security greatly by improving recognition accuracy of authorised drivers and passengers. For the system to fail, both detectors (face recognition camera and registration plate camera) must fail. Hence, the probability of error for the combined recognition system, using two detection methods, is the product of the individual detector probabilities of error.
For example, if both facial recognition camera and registration plate camera have a 95% probability of accuracy, the dual-detector (dual camera system) has a probability accuracy rate of 99.75%
In addition, multiple detectors increase the robustness of the security system. If there is a technical problem reducing capabilities of one piece of equipment, the other parts of the system can still provide some security assurance.
To recognise cars, several technologies are effective … the most flexible being a registration plate reader, as it doesn’t require any co-operation by drivers, or any additional equipment for their cars. Registration plate reading technology is now widely used and very effective in lanes or when approaching gates and barriers.
Again, the system utilises a camera aided by LED lighting to get a good registration plate image and also Optical Character Recognition
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(OCR) tuned for accuracy in reading registration plate characters.
Registration plate readers also use watch lists of known vehicles, including those owned by authorised employees, and, if required, can use those known to be associated with protestors, criminals and suspected terrorists.
Generally, for operation at a specific location, two cameras are required, one for facial recognition and one for registration plate reading. The two cameras must be directed at different angles and positioned in different locations, so often two discreet mounting poles are used (if the cameras cannot be fitted to the building’s fabric at the entrance).
If rear-seated passengers are to be detected, an additional two cameras is normal, and if the underside of the vehicle is to be captured and available for instant comparison in future, a scanning set of cameras is fitted on the roadway.
To fully automate the system, a pressure sensor or beam device can be used to detect each passing vehicle and trigger the cameras at appropriate times, allowing the system to automatically:
• record images (of registration, driver and passengers) and under-vehicle image (if fitted)
• immediately initiate facial recognition and registration plate recognition (and under vehicle image recognition if fitted)
All of the above takes less than 3 seconds.
If the database of authorised personnel is available, the system will immediately check driver, passengers and vehicle images … this is instant.
If the images of vehicle, registration plate and driver/passengers are not in the database already, they can be automatically captured and stored (enrolling the driver with the vehicle’s details) whilst security is assured using the manual standard operational process by the guard. Once the guard is satisfied that the driver/passengers and
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vehicle should be granted access and be enrolled on the system as authorised, this can be done quickly and immediately, and in future the system will automatically check and grant/deny access on the basis of the updated information given to the database.
In this way, the system is self-learning and a database can be built up of authorised personnel and their associated vehicles.
In the relatively rare case that an unauthorised driver and a vehicle must be turned around at the gate/barrier, the guard will be able to annotate that unauthorised driver’s photo and vehicle registration by clicking an icon on the photo, and the database can automatically record/add that person to a ‘watch list’.
This method of creating a database through use is akin to machine learning. It makes the system quickly capable whether facilities have existing data or not (very useful for building databases of visiting delivery vehicles or maintenance contractors) whilst eliminating the problem that an existing database might contain old or otherwise bad data.
Over time, enrolment can be tapered off, updating information for authorised drivers only occasionally to maintain current images.
In addition to the added security described above, should the threat level or security requirement warrant it, the system can be augmented to operate with ‘automated foreign object detection’ under the vehicle and X-Ray of the vehicle itself to detect anomalies inside the vehicle.
Drivers are unlikely to object to this use of facial recognition technology because they get immediate benefits: Faster Throughput and Better Security.
Dave Harmon Director, Business Development, UK & Europe Gatekeeper Security
www.gatekeepersecurity.com > 25
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