Year: 2024
Type: article
Abstract: 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.
DOI: 10.3169/mta.13.119
Authors: Ryotaro Ooe, Kazuhiro Fujita, Koji Shinomiya
Institutions: Ryukoku University, Hyogo Prefectural Police
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405947020