Pengenalan Karakter Plat Nomor Mobil Secara Real Time
Ikhwan Ruslianto(1*), Agus Harjoko(2)
(1) 
(2) 
(*) Corresponding Author
Abstract
Abstrak
Pengenalan plat nomor di Indonesia biasanya digunakan pada sistem parkir yang masih dilakukan secara manual, yaitu dengan mencatat karakter plat nomor oleh petugas jaga parkir. Padahal pengenalan plat nomor tidak hanya dilakukan untuk system perparkiran tetapi dapat digunakan untuk menemukan kendaraan yang melanggar peraturan lalu lintas dijalan raya secara real time, misalnya pelaku tabrak lari pada kecelakaan maupun kendaraan yang melanggar rambu-rambu lalu lintas.
Penelitian ini memberikan alternatif pengenalan karakter plat nomor mobil menggunakan metode connected component analysis dan matching sehingga dapat menyelesaikan permasalahan dengan background yang kompleks dan mobil yang bergerak dijalan raya.
Metode connected component analysis berhasil melakukan proses segmentasi plat dan segmentasi karakter dengan kondisi background yang kompleks secara tepat terhadap 67 sampel citra dengan tingkat keberhasilan 95,52% untuk segmentasi plat dan 94,98% untuk segmentasi karakter dan metode template matching berhasil melakukan proses pengenalan karakter secara akurat dengan tingkat keberhasilan 87,45%.
Kata kunci— real time, connected component analysis, template matching
Abstract
Indonesia’s number plat recognition system are typically used in parking lots that are still done manually, by recording the license plate characters by parking guard. Though number plate recognition system is not only for parking but can be used to find vehicles that violate traffic rules highway street in real time, such as actors on the hit and run accident and the vehicles that violate traffic signs.
This study provides an alternative car number plate character recognition using connected component analysis and matching so as to solve problems with complex background and a moving car on the road.
Connected component analysis method successfully to the plates segmentation and character segmentation in complex background condition are appropriate to the 67 sample images with the success rate of 95.52% for the plate segmentation and 94.98% for plate character segmentation and template matching method successfully perform the character recognition process accurately with a success rate of 87.45%.
Keywords— real time, connected component analysis, template matchingFull Text:
PDFDOI: https://doi.org/10.22146/ijeis.1967
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