Question, from a technical perspective, how much of your fuzzy/unclear plate problem do you think will be solved by advances in cameras? In the context of a car with 4 to 6 cameras mounted on it roving a parking lot checking plates. Already the video output from the hdmi port on a GoPro hero7 black is considerably better than what a $4000 camera could do just 3.5 years ago, and it costs $349... Or various setups I have seen with modified 22 megapixel Sony mirrorless cameras used for GIS orthophotos from drone platforms.
Hard to say. FWIW, much of the time the exact plate gets read. But it also matters what has been trained. Some states have weird vanity plates. So it not purely an optics problem.
If I could I would have all my customers scan plates with the iPhone XS. But many work with 7 or even less.
Also introducing a lot more collected data to dedupe is a thing as well. One of the first algos I worked on was just realizing in short term new dats we already had a car and to not try and treat the same car like it was another car.
Are there ALPR companies with a workflow where the truly unrecognizable plates go in a review queue for image recognition by a human offshore somewhere, in a low cost location? I'm thinking of the standard call centre salary for people with an average level of education in second/third-tier cities in India, in Pakistan, in Bangladesh, etc.
