Real-time search-free multiple license plate recognition via likelihood estimation of saliency. (November 2016)

• Record Type: Journal Article
• Authors: Safaei, Amin; Tang, Hongying L.; Sanei, Saeid
• Is Part Of: Computers & electrical engineering. Volume 56(2016)
• Page Start: 15
• Page End: 29
• Publication Date: 2016-11
• Subjects: Automatic license plate recognition -- Bayesian -- Intelligent transportation system -- Localization -- Object tracking -- Saliency map detection -- Shadow removal; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2016.09.010
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: A search-free car license plate localization method based on 3-D Bayesian saliency estimation has been developed for the first time. This method uses a 3-D object tracking algorithm based on Bayesian methods to estimate the 3-D salient regions by exploiting the motion information in the videos. The algorithm is fast and robust to variation in the environment and is suitable for localizing multiple plates. The tracking approach exhibits acceptable accuracy for different noise and artefact levels. The localization method uses adaptive size in closing to improve the accuracy. Graphical abstract: Abstract: In this paper, we propose a novel search-free localization method based on 3-D Bayesian saliency estimation. This method uses a new 3-D object tracking algorithm which includes: object detection, shadow detection and removal, and object recognition based on Bayesian methods. The algorithm is tested over three image datasets with different levels of complexities, and the results are compared with those of benchmark methods in terms of speed and accuracy. Unlike most search-based license-plate extraction methods, our proposed 3-D Bayesian saliency algorithm has lower execution time (less than 60 ms), more accuracy, and it is a search-free algorithm which works in noisy backgrounds.