The 11th Iranian and the first International Conference on Machine Vision and Image Processing

Iranian License Plate Recognition UsingDeep Learning

Atefeh Ranjkesh Rashtehroudi, Asadollah Shahbahrami, Alireza Akoushideh
The 11th Iranian and the first International Conference on Machine Vision and Image Processing (MVIP 2020)

Abstract

Automated License Plate Recognition (ALPR) has many applications in intelligent transport system. The ALPR has three main steps, License Plate (LP) localization, segmentation and Optical Character Recognition (OCR). Each step needs different techniques in real condition and each technique has its specific characteristics. The LP localization techniques detect the LP after that segmentation algorithms should segment and isolate each character from each other. Finally, the OCR step is applied to recognize the separated characters. The final accuracy depends on the accuracy of each step. To improve the OCR step performance, we combine both segmentation and OCR steps as a single-stage using deep learning techniques such as the You Only Look Once (YOLO) framework. Our experimental results show that this proposed approach recognizes the Iranian LP characters with accuracy 99.2% compared to previous works.

Keywords: Optical Character Recognition, Deep Learning, YOLO, Artificial Neural Network, Support Vector Machine



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