Automatic Number Plate Recognition using Region-based Convolution Neural Network and LSTM
Automatic Number plate recognition is the most extensive practice used in diversified ways to identify an
image of vehicles number. This practice has undergone many technologies to overcome significant
drawbacks over the years. One of the major concerns observed is the recognition and sequencing of the
number plate. Although the identification is not a primary apprehension, the object recognition and order
of the number plate is the most important alarm.
So considering this problem the present paper deals with R-CNN and LSTM to identify and recognition of
an image of the number plate. In this method, the arbitrary sequence of the number and the exact text
analysis in a particular format is safeguarded. The combination of both Convnet and Recurring Neural
Network with LSTM result in a accurate numbers of vehicles.