Plate.Vision is a vehicle identification software through license plate recognition,

Today we are accessible to a mountain of intelligent technologies. And no doubt that computer vision stores a vital space among all of them. When we talk about computer vision, the foremost application that we think of is Image Recognition. But indeed, a computer vision also encompasses OCR (Optical Character Recognition) algorithm, which allows seamless computer operations. In this article, we will discuss the origin, advancements, OCR tasks, and OCR industry applications that are enriching the OCR Pipeline.

To actually detect and recognize number plates in an input image a network much like the above is applied to 128x64 windows at various positions and scales, as described in the windowing section. The network differs from the one used in training in that the last two layers are convolutional rather than fully connected, and the input image can be any size rather than 128x64. The idea is that the whole image at a particular scale can be fed into this network which yields an image with a presence / character probability values at each "pixel". The idea here is that adjacent windows will share many convolutional features, so rolling them into the same network avoids calculating the same features multiple times.