Vehicle plate number localization using a modified GrabCut algorithm

Vehicle plate number recognition plays an important role in traffic control and surveillance systems. A key stage in any vehicle plate number recognition system is to first locate the vehicle plate number. In this paper, we present a modified GrabCut algorithm for localizing vehicle plate numbers. In contrast with the traditional interactive GrabCut technique, a modified GrabCut algorithm was designed to identify and extract vehicle plate numbers in a completely automatic manner. Our approach extends the use of the traditional GrabCut algorithm with addition of a feature extraction method which uses geometric information to give accurate foreground extraction. Finally, to evaluate the performance of the proposed technique, the localization accuracy is tested with a dataset of 500 vehicle images with vehicle plates from different countries. An accuracy of 99.8% was achieved for the localization of vehicle plates. Comparative analysis is also reported. (c) 2019 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This study introduced a modified GrabCut algorithm to localize vehicle plate numbers, achieving a high localization accuracy of 99.8%, and conducted comparative analysis with traditional methods.