Hi,
I've been reading a lot lately in order to train OpenCV to find number Australian number plates in an image. I was just wondering : from what I understand of the training process, you provide a lot of real life images of the object you want to train your detector for (I have access to thousands of images that's fine) in different conditions..
Now, a number plate is, by essence, unique. So just out of curiosity here (because I know some LBP detector do work for ANPR) : is that why the detector need soooo many examples ? Would not it be "easier" to train it to find objects looking like number plates : find the rectangular shape but not caring about "what's inside" ?
Maybe I got it all wrong; I just woke up with this question in my head seeing my training having run for 16hours and still in phase 1 ^^
Cheers guys.