Research advanced in deep learning-based licence plate recognition and localization

Abstract

The purpose of licence plate recognition is to analyze pictures or videos of moving vehicles to read the plate and identify the vehicle's owner. Traffic data management and smart transportation systems rely heavily on licence plate reading technology. Initial picture capture, image preprocessing, licence plate analysis, character segmentation, and recognition are the building blocks of licence plate recognition. The present analysis centres on the examination of the above key steps. In this paper, we introduce the latest research progress in the implementation of licence plate recognition utilizing deep learning techniques, including the classic framework of licence plate location and character recognition, representative methods, and their advantages and disadvantages. We also perform a quantitative comparison of existing representative methods. Finally, we summarize the challenges in the research domain of licence plate recognition and discuss the future development direction from the aspects of neural network interpretability, more general small sample learning methods, and incremental learning.