Efeler, Mahmut Cenk

Profile URL
https://hdl.handle.net/11147/16141
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Email Address
mahmutefeler@iyte.edu.tr
Main Affiliation
03.05. Department of Electrical and Electronics Engineering
Status
Current Staff
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ORCID ID
0000-0003-4703-8228
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Turkish CoHE Profile ID
D206F1153AD9F508
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WoS Researcher ID
ESB-9378-2022

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2013 21st Signal Processing and Communications Applications Conference, SIU 20131
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  • Conference Object
    A Bayesian Approach for Licence Plate Recognition Developed on a Realistic Simulation Environment
    (Institute of Electrical and Electronics Engineers Inc., 2013) Efeler, Mahmut Cenk; Altınkaya, Mustafa Aziz; Gümüştekin, Şevket
    Template matching is one of the most common methods for license plate recognition. This method discards prior probabilities of license plate codes. The posterior code class probabilities constructed by including the prior probability information are expected to improve the recognition performance. The probability information that needs to be included requires extensive training data, which is quite costly to obtain. In order to generate these training images a license plate image simulator is developed with a realistic noise model. Simulated license plate images are then used to test a Bayesian decision theory based recognition procedure. Test results indicate that, with the inclusion of prior information, significant recognition gain is obtained with respect to standard template matching method at high noise levels.