Dinanta, Fakhri Athaya (2022) Sistem Pengenalan Pelat Nomor Kendaraan Secara Real Time untuk Aplikasi Smart Parking. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Sistem tempat parkir yang ada di Indonesia kebanyakan masih melakukan pencatatan pelat nomor secara manual dengan bantuan manusia. Hal ini dirasa kurang efektif apabila tempat parkir tersebut akan menerapkan sistem tempat parkir cerdas (smart parking). Oleh sebab itu, diperlukan suatu cara yang dapat menggantikan peran orang tersebut untuk mendeteksi dan mengenali pelat nomor kendaraan. Salah satu caranya adalah menggunakan sistem Real-Time Automatic Number Plate Recognition yang memafaatkan teknologi Optical Character Recognition (OCR). Teknologi OCR merupakan teknologi yang dapat mengenali teks pada suatu citra digital.
Sistem yang diajukan pada penelitian ini merupakan sistem pendeteksian dan pengenalan karakter pelat nomor secara real-time. Sistem ini akan mendeteksi pelat nomor mobil dari akuisisi kamera yang terhubung dengan sistem ANPR. Sistem ini dapat mengenali pelat nomor dengan berbagai warna dasar dan warna karakter serta jenis huruf yang digunakan. Setelah dilakukan pengujian, kesuksesan pendeteksian citra real-time mencapai 45% dari total citra yang terakusisi dan 70% untuk citra digital berupa gambar.
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The majority of parking spots in Indonesia still manually record the cars number plate with the help of human. This thing is considered not efficient if that parking spot wants to implement smart parking system. Therefore, it needs a method that can replace the role of human to detect and recognize the vehicles number plates. One of them is using real-time Automatic Number Plate Recognition System or ANPR that utilizes Optical Character Recognition (OCR) technology. OCR technic can recognize texts on a certain digital image.
The proposed system on this research is a real-time number plate detection and recognition system. The system can detect and recognize number plates from the acquired images from camera that connects with the ANPR system. This system can recognize number plates with various plate and character colour and also various character font. After the expiriment is done, the success rate of real-time detection is about 45%. Meanwhile, the success rate of image detection is 70%.
Item Type: | Thesis (Other) |
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Uncontrolled Keywords: | ANPR, OCR, Smart Parking |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication |
Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
Depositing User: | Fakhri Athaya Dinanta |
Date Deposited: | 03 Feb 2022 02:52 |
Last Modified: | 31 Oct 2022 02:48 |
URI: | http://repository.its.ac.id/id/eprint/92669 |
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