An Effective and Fast Iranian License Plate Detection Using Statistical and Geometrical Approaches

• Autorzy: Poursiyah Saman , Salami Hosian , Mohebbi Mohamad Reza , Tabatabaee Hamid

Identyfikatory

DOI

10.12913/22998624/100345

• Języki publikacji: EN

Abstrakty

EN

The first step in the process of detection a license plate is to determine the location of the plate. The output of this stage should be accurate enough and calculations will be completed within a short time. The reason for this is that the output of this stage is as input in the next steps. If the step to determine the location is encountered error, then the operation of the next steps will also be interrupted. In this paper, a new method is used to improve the contrast of the image, delete non-numeric characters, analysis and clustering of plain characters in order to determine the location of an Iranian car license plate with dark characters, a clear background is provided. The proposed method reduces the overall complexity of the algorithm and in addition to its ease of implementation, the system’s speed and efficiency improve the location of the plate. The proposed algorithm is independent of the number of vehicle plates in the image, image size, complete unread plate and in contrast to brightness variations, it is largely resistant. The results of the test on two different data sets with 67 and 492 images, to an accuracy of 100 and 99.59 percent with an error rate of 1.5 and 1.63 and the runtime of 109 and 17.5 milliseconds averaged, were achieved.

Słowa kluczowe

EN

determine location of license plate; adaptive contrast stretch; character analysis and clustering

PL

tablica rejestracyjna; określanie lokalizacji; zastosowanie kontrastu

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2018
• Tom: Vol. 12, no 4
• Strony: 115--125
• Opis fizyczny: Bibliogr. 27 poz., fig., tab.

Twórcy

autor

Poursiyah Saman

• Department of Computer Engineering, Quchan Branch, Islamic Azad University, Quchan, Iran

autor

Salami Hosian

• Department of Computer Engineering, Ferdows Institute of higher Education, Mashhad, Iran

autor

Mohebbi Mohamad Reza

• Department of Computer Engineering, Ferdows Institute of higher Education, Mashhad, Iran

autor

Tabatabaee Hamid

• Department of Computer Engineering, Quchan Branch, Islamic Azad University, Quchan, Iran

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).