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This paper presents a novel approach for Indian Number Plate Recognition using the Convolution Neural Network (CNN). We generated and augmented synthetic data in Indian standards with variant background and font. We also collected and labelled real data of Indian License plates to create a genuine Indian oriented dataset. We compared existing models like SVM, KNN and CRNN in terms of accuracy and inference time, and selected LPRNet. We first trained the existing LPRNet model, which is designed for Chinese License plates on synthetic data and secured 85% accuracy. We then modified the LPRNet model and secured 93% accuracy on the same synthetic data. We applied the post-processing technique of pattern recognition rules for Indian standards of License plates to further improve accuracy. The Proposed system achieved 95% accuracy after fine-tuning with real data. Our model is very lightweight and can easily be deployed on Nvidia-Jetson nano, Intel Neural Compute Stick.

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