Risky, Ari Wibowo (2024) PENGENALAN PELAT NOMOR KENDARAAN MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK UNTUK OPTICAL CHARACTER RECOGNITION. S1 thesis, Fakultas Teknik Universitas Sultan Ageng Tirtayasa.
![[img]](https://eprints.untirta.ac.id/style/images/fileicons/text.png) |
Text (Fulltext)
Risky Ari Wibowo_3332190086_Fulltext.pdf Restricted to Registered users only Download (1MB) | Request a copy |
|
Text (Bab 1)
Risky Ari Wibowo_3332190086_01.pdf Restricted to Registered users only Download (475kB) | Request a copy |
|
Text (Bab 2)
Risky Ari Wibowo_3332190086_02.pdf Restricted to Registered users only Download (106kB) | Request a copy |
|
Text (Bab 3)
Risky Ari Wibowo_3332190086_03.pdf Restricted to Registered users only Download (302kB) | Request a copy |
|
Text (Bab 4)
Risky Ari Wibowo_3332190086_04.pdf Restricted to Registered users only Download (510kB) | Request a copy |
|
Text (Bab 5)
Risky Ari Wibowo_3332190086_05.pdf Restricted to Registered users only Download (8kB) | Request a copy |
|
Text (Daftar Referensi)
Risky Ari Wibowo_3332190086_Ref.pdf Restricted to Registered users only Download (146kB) | Request a copy |
|
Text (Lampiran)
Risky Ari Wibowo_3332190086_Lamp.pdf Restricted to Registered users only Download (458kB) | Request a copy |
|
Text (Fulltext Turnitin)
Risky Ari Wibowo_3332190086_CP.pdf Restricted to Registered users only Download (14MB) | Request a copy |
Abstract
The increase in vehicle ownership every year causes the lack of information monitoring on each vehicle to decrease. As one of the methods used to find out vehicle information, recognizing each number plate is a solution for recognizing vehicles. Utilizing object detection techniques using computer vision in recognizing vehicle number plates can simplify the plate recognition process. The process of identifying and classifying the characters on the plates is carried out simultaneously with a simple implementation which is a benefit of using computer vision in recognizing vehicle plates. The use of the Haar cascade classifier algorithm in this research overcomes the problem of plate detection combined with the CNN algorithm to identify OCR characters on vehicle plates. The results of vehicle plate recognition experiment in 4 real-time tests obtained an average accuracy value of 42.67%.
| Item Type: | Thesis (S1) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Contributors: |
|
|||||||||
| Additional Information: | Peningkatan kepemilikan kendaraan setiap tahunnya menyebabkan kurangnya pengawasan informasi pada setiap kendaraan menjadi menurun. Sebagai salah satu bentuk metode yang digunakan untuk mengetahui informasi kendaraan, pengenalan setiap pelat nomor menjadi sebuah solusi dalam mengenali kendaraan. Pemanfaatan teknik pendeteksian objek dengan menggunakan visi komputer dalam pengenalan pelat nomor kendaraan dapat mempermudah proses pengenalan pelat. Proses identifikasi dan klasifikasi karakter pada pelat dilakukan secara bersamaan dengan implementasi sederhana menjadi suatu manfaat penggunaan visi komputer dalam mengenali pelat kendaraan. Penggunaan Algoritma Haar cascade classifier pada penelitian ini mengatasi permasalahan pendeteksian pelat yang digabungkan dengan algoritma CNN untuk mengidentifikasi karakter secara OCR pada pelat kendaraan. Hasil pengujian pengenalan pelat kendaraan pada 4 pengujian secara langsung didapatkan nilai akurasi rata-rata 42,67%. | |||||||||
| Uncontrolled Keywords: | Pengenalan Pelat, Deteksi Objek, Haar cascade, CNN, OCR Pelat | |||||||||
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | |||||||||
| Divisions: | 03-Fakultas Teknik > 20201-Jurusan Teknik Elektro | |||||||||
| Depositing User: | RISKY ARI ARI WIBOWO | |||||||||
| Date Deposited: | 25 Nov 2024 09:34 | |||||||||
| Last Modified: | 25 Nov 2024 09:34 | |||||||||
| URI: | http://eprints.untirta.ac.id/id/eprint/44123 |
Actions (login required)
 |
View Item |