By Christian Laforte
Panic and surprise
Three days ago I received a panicked call from my wife. She had been arrested while driving on the highway near the office in Montreal, Canada with our 10-months old daughter. I ran to the scene and was told by the policeman that my wife drove safely, but we had neglected to renew our license plate on time. We had to accompany him to the police station and pay $600 in fines and towing charges.
Not the actual scene, but you get the idea.
How could this happen? We always pay our bills right away. We notified the government of our new address before moving apartment last year. But more interesting to the readers of this blog, how did the police identify my wife’s car out of the dozens that pass every minute on the highway?
The policeman — let’s call him Joe — gave me a lift to the traffic authorities, and explained how this all works. A real-time license plate scanner is installed on a patrol car on the side of the highway. Using an active light source and high-speed cameras, it tracks every license plate that passes and compares it against an on-board database, updated once a week through a USB key. The device costs $25,000.
“Isn’t that expensive?”, I asked Joe.
“Listen to the radio… They just arrested a guy who already lost his permit. He was driving a car with an expired license plate and he was wanted for petty crimes and unpaid parking tickets. He’s looking at a fine of at least $900, plus the old parking tickets. We would have never caught the guy otherwise. No wonder the big boss wants to equip at least 100 cars with the device by the end of year.”
Frustration instantly switched into interest (and a bit of envy)
That’s a market of $2.5M for a small city like Montreal. A great market for a computer vision technology, with a lot of potential growth in years to come.
Still until now, I’ve always been an optimistic proponent of computer vision technologies. I wasn’t too worried about privacy. Being arrested certainly gave me a fresh perspective. Especially, as it turns out, because the government admitted having a bug in their address change software, which explained why we never got the license plate renewal notice.
Anyway, I still love computer vision and this is a cool technology, so let’s explore how it works and how it could be improved.
Description of the system
I haven’t seen the system but on the spot I asked Joe a lot of questions to have a better idea. The device is bolted on the roof of another patrol car, stopped on the highway. It has two cameras and one red, intense light source, like those used in barcode scanners. The cameras and the light source are tuned to focus on highly reflective surfaces, like a clean license plate. It can be fooled if the license plate is dirty or if there are other highly reflective surfaces in the field of view, e.g. a policeman badge, or I assume, when the sun reflects toward the camera. Otherwise the system appears quite robust: it works night and day, it can deal with partial occlusions of the license plate, and it can read multiple license plates in the same image.
Limitations of the system
- The database is only updated once a week. People can get arrested more than once even though they paid the fine.
- The device only scans plates. It cannot recognize a stolen car with a valid plate. As Joe explained, organized criminals are smart: they wouldn’t risk getting arrested with a false or expired plate.
- The device, I presume, can be fooled easily by adding a filter (e.g. transparent film or grease) on the plate to absorb the red wavelength, or by adding a mirror next to it to distract the cameras. To the human eye, the plate would look fine, but it would no longer be detected by the device.
- Joe explained that, if the driver were to speed away, he probably couldn’t do anything. The police no longer engage in speed chases since it’s too dangerous for the police and the general public. They have a hard time tracking dangerous drivers that speed away.
Clearly, recognizing a license plate is too simplistic. Pretty soon, criminals will know how to fool the system and the only honest people like my wife will be apprehended.
A better solution
For a device like this to be truly useful, it would first need to be connected to the central station database. Just plug it into a cellular network, e.g. using an iPhone or Android (link). With a fast enough connection, the video stream could be uploaded, recorded and processed in a central server farm. This could vastly reduce the size and cost of the device and increase the recognition capability of the overall system. The cheaper system could be installed on every patrol car or traffic light. A dangerous driver speeding away could be tracked across the city and apprehended when finally stops.
Using high resolution cameras, It would be pretty easy to recognize a car color, brand and year from the video stream: all you need is a database of logos and a good feature detector. Getting this to run at real-time would be challenging, but I’m confident this can be achieved given a year or two of development. Looking at the car as a whole would help identify stolen vehicles.
Pushing this farther, cars could be tracked across an entire city, e.g.: London with its networks of surveillance cameras. Criminals could be followed to their lair hours after a crime is reported. Hopefully the people in charge will re-think the overall process so honest people aren’t harassed or tracked without a good reason.
(Note: this is a draft of the post. I haven’t had the time to research the solution, but I’m posting it early anyway since the Washington post and Slashdot just featured a similar story.)
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