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dc.contributor.authorEfeler, Mahmut Cenk
dc.contributor.authorAltinkaya, Mustafa A.
dc.contributor.authorGumustekin, Sevket
dc.description21st Signal Processing and Communications Applications Conference (SIU)en_US
dc.descriptionAltinkaya, Mustafa A/0000-0001-8048-5850en_US
dc.description.abstractTemplate 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.en_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.subjectlicense plate recognitionen_US
dc.subjectBayesian pattern recognitionen_US
dc.titleA Bayesian Approach for Licence Plate Recognition Developed on a Realistic Simulation Environmenten_US
dc.relation.journal2013 21St Signal Processing And Communications Applications Conference (Siu)en_US
dc.contributor.departmentIzmir Isntitute of Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US

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