Leveraging Model Fusion for Improved License Plate Recognition

Abstract

License Plate Recognition (LPR) plays a critical role in various applications, such as toll collection, parking management, and traffic law enforcement. Although LPR has witnessed significant advancements through the development of deep learning, there has been a noticeable lack of studies exploring the potential improvements in results by fusing the outputs from multiple recognition models. This research aims to fill this gap by investigating the combination of up to 12 different models using straightforward approaches, such as selecting the most confident prediction or employing majority vote-based strategies. Our experiments encompass a wide range of datasets, revealing substantial benefits of fusion approaches in both intra- and cross-dataset setups. Essentially, fusing multiple models reduces considerably the likelihood of obtaining subpar performance on a particular dataset/scenario. We also found that combining models based on their speed is an appealing approach. Specifically, for applications where the recognition task can tolerate some additional time, though not excessively, an effective strategy is to combine 4-6 models. These models may not be the most accurate individually, but their fusion strikes an optimal balance between speed and accuracy.

arXiv commentAccepted for presentation at the Iberoamerican Congress on Pattern Recognition (CIARP) 2023

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Cited by in corpus (8)

• Enhancing License Plate Super-Resolution: A Layout-Aware and Character-Driven Approach
• Toward Advancing License Plate Super-Resolution in Real-World Scenarios: A Dataset and Benchmark
• Multi-Feature Aggregation in Diffusion Models for Enhanced Face Super-Resolution
• Toward Enhancing Vehicle Color Recognition in Adverse Conditions: A Dataset and Benchmark
• Improving Small Drone Detection Through Multi-Scale Processing and Data Augmentation
• Advancing Multinational License Plate Recognition Through Synthetic and Real Data Fusion: A Comprehensive Evaluation
• LPLC: A Dataset for License Plate Legibility Classification
• Toward Unified Fine-Grained Vehicle Classification and Automatic License Plate Recognition