[Paper] Discriminating Car License Plate Numbers on Low Resolution Using Sparse PCA
License plates captured in surveillance videos often have insufficient resolution, making it difficult to recognize the numbers. In this paper, we propose a novel method for license plate number recognition using sparse PCA coefficients and Naive Bayes classifier. The proposed method is applied to low-resolution license plate images, and its performance is compared with two conventional methods: moment features with Bayes classifier and PCA coefficients with naive Bayes classifier. The evaluation results, including the first-candidate recognition rate, the recognition rate up to the second candidate, and the classification cross-entropy, show that the proposed method achieves the best performance.
Authors
- Koji Shinomiya
- Kazuhiro Fujita
- Ryotaro Ooe
Institutions
- Ryukoku University (JP)
- Hyogo Prefectural Police (JP)
Publication Details
- Journal
- ITE Transactions on Media Technology and Applications
- Published
- 2024-12-31
- DOI
- https://doi.org/10.3169/mta.13.119
- Primary Topic
- Vehicle License Plate Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.00