Text Recognition in Moving Vehicles using Deep learning Neural Networks

This paper presents a method of text characters and numbers recognition system in number plates of moving vehicles. The system includes a camera connected to Raspberry-Pi which captures the video of moving vehicles. Frames containing the number plate pictures of the vehicles are extracted from the video and then preprocessed for improving the clarity and reduce blur. The region containing the text is segmented and applied to classification network. In this work, deep residual network or ResNet-34 Convolutional neural network architecture, which consists of 34 layers, is employed for feature extraction and identification of characters in the vehicle number plate images. Automatic vehicle number detection systems have widespread applications in Highway Toll collection, Tracking entry and exit of vehicles in Official places, apartments, etc. and could reduce manpower and reduces inconvenience caused to passengers..