Robust search-free car number plate localization incorporating hierarchical saliency

Safaei, A. ORCID: 0000-0003-4696-8968, Tang, H.L. and Sanei, S. ORCID: 0000-0002-3437-2801, 2016. Robust search-free car number plate localization incorporating hierarchical saliency. Journal of Computer Science & Systems Biology, 9 (3), pp. 93-103. ISSN 0974-7230

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Abstract

There are two major shortcomings associated with presently implemented automatic license plate recognition (ALPR) systems: first, processing images with complex background is time-consuming and second, the results are not sufficiently accurate. To overcome these problems and also to achieve a robust recognition of multiple car number plates, saliency detection based on the ALPR system is used in this paper and also an improved and more effective definition of saliency is presented. In this new approach, the notion of the directionality of the edges using Gabor filtering and the detection of the patterns of numbers using L1 -norm have been added to the traditional saliency detection method. The proposed algorithm was tested on 660 images; some consisting of two or more cars.
A detection accuracy of 94.77% and an average execution time of 40 ms for 600 × 800 images are the marked outcomes. The proposed SB-ALPR method outperforms most of the state of the art techniques in terms of execution time and accuracy, and can be used in real-time applications. Also, unlike some recently introduced saliency-based ALPR methods, our two-stage saliency detection approach exploits smaller numbers of sample sizes to reduce the computation cost.

Item Type: Journal article
Publication Title: Journal of Computer Science & Systems Biology
Creators: Safaei, A., Tang, H.L. and Sanei, S.
Publisher: Omics Publishing Group
Date: 5 April 2016
Volume: 9
Number: 3
ISSN: 0974-7230
Divisions: Schools > School of Science and Technology
Depositing User: Jill Tomkinson
Date Added: 13 Feb 2018 16:21
Last Modified: 31 Aug 2018 13:57
URI: http://irep.ntu.ac.uk/id/eprint/32694

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