It will be impossible to guarantee anywhere close to a 100% matching record in real-world scenarios. Be careful with size and ratio issues because some legal number plates can be dramatically different sizes and ratios. Such as the "Q" plates, (Qld) and things like Trailer/Bike Rack plates out on the roads.
If you're getting a reasonable hit rate, and ensuring that you're are getting nearly all plates plus a few false-positives, then process/OCR all hits and pick the "best" match. In cases where you detect false-positives, but find a single match for plate suspect, flag them for review. (low urgency) Cases where you get no match, or multiple matches, flag for review at high urgency.
You can prioritize placement in the image (depending on whether you're capturing front or back images, front should be easier for placement) but again this cannot be too strict as trucks and bike-racks can have plates in less expected regions of the image, plus people that put them in the rear window. (no idea how legal that is.)
On a non-technical note, if you have control over the hardware then be sure to use an Infra-red camera. Plates are manufactured using IR reflective inks. (usually the background) This aides OCR contrast, but also filters out personalized backgrounds from the images. (So Daffy's face doesn't mess up the OCR.)