Automatic number plate recognition using CNN based self synthesized feature learning

In today's image centric world image processing has become the centre of attention for various real-life applications. Embarking from car thefts, breaking traffic rules to contravene restricted expanse, Image Processing has given us a conviction to put a grinding halt to these malpractices. Inspired by the feature learning capabilities of Convolution Neural Networks (CNN), the preeminent work is the detection and recognition of the car plate number image which is accomplished by dint of Convolution Neural Network (CNN). The number plate images can be procured by a still camera. Self synthesized feature of CNN is capable of recognizing the states of the vehicle from the number plate with a reasonably high accuracy of 90% even with very low training size. CNN has proved its robustness even with distorted, tilted and illuminated datasets.