PERANCANGAN SISTEM DETEKSI PLAT KENDARAAN BERMOTOR MENGGUNAKAN OPENCV BERBASIS WEB
DOI:
https://doi.org/10.33884/comasiejournal.v11i4.9127Kata Kunci:
Computer Vision, Open CV, Object Detection, NodeMCU ESP8266, Digital ImageAbstrak
This research aims to design a motor vehicle license plate detection system using web-based OpenCV, applied in the Sandona residential complex, Batam. This system replaces access cards for entry, enhancing security by automatically detecting registered vehicle license plates. If registered, the gate opens automatically. The methodology includes preliminary studies, literature review, preparation of tools and materials, design, as well as testing and analysis. The system uses NodeMCU ESP8266, a webcam, a servo motor, an ultrasonic sensor, and software developed with Python and OpenCV for image processing. The detection process involves capturing images of license plates, processing the images to extract numbers, and matching them with a database for validation. Testing results show an accuracy rate of 75% under optimal conditions. Accuracy is influenced by the position of the license plate, which must be upright and straight to the camera, as well as adequate lighting conditions. Under ideal conditions, the system works well and can improve access efficiency and security in the Sandona residential complex.
Keywords: Computer Vision, Digital Image, NodeMCU ESP8266, Object Detection; Open CV.
Referensi
Afrizal, F., & Prastowo, B. N. (2022). Vehicle Detection System Using Ultrasonic And Magnetic Fields Sensors Based On LoRa Communication. IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), 12(2), 157. https://doi.org/10.22146/ijeis.71725
Hanif, A. R., Nasrullah, E., & Setyawan, F. X. A. (2023). Deteksi Karakter Plat Nomor Kendaraan Dengan Menggunakan Metode Optical Character Recognition (Ocr). Jurnal Informatika Dan Teknik Elektro Terapan, 11(1), 109–117. https://doi.org/10.23960/jitet.v11i1.2897
He, Y., Zhao, L., & Zou, C. (2006). Face recognition using common faces method. Pattern Recognition, 39(11), 2218–2222. https://doi.org/10.1016/j.patcog.2006.04.037
Hidayat, R., Wagyana, A., Studi, P., Multimedia, B., Elektro, J. T., & Jakarta, N. (2018). Rancang Bangun Sistem Presensi Menggunakan Face Recognition dengan Metode Eigenface. Agus Wagyana / Jurnal Ilmiah Setrum, 7(2), 278–287.
Illmawati, R., & Hustinawati. (2022). YOLO v5 untuk Deteksi Nomor Kendaraan di DKI Jakarta. Journal of Information System Research (JOSH), 10(1), 32–43.
Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You only look once: Unified, real-time object detection. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016-Decem, 779–788. https://doi.org/10.1109/CVPR.2016.91
Saragih, S. P. (2024). Desain Sistem Informasi Penyaluran Tenaga Kerja (studi kasus: PT. xyz Penyalur Asisten Rumah Tangga). Jurnal Desain Dan Analisis Teknologi, 3(2), 163–168. https://doi.org/10.58520/jddat.v3i2.65
Satya, L., Septian, M. R. D. S., Sarjono, M. W., Cahyanti, M., & Swedia, E. R. (2023). Sistem Pendeteksi Plat Nomor Polisi Kendaraan dengan Arsitektur Yolov8. Sebatik, 27(2), 753–761. https://doi.org/10.46984/sebatik.v27i2.2374
Wakhidah, N. (2012). Deteksi Plat Nomor Kendaraan Bermotor Berdasarkan Area pada Image Segmentation (Licence Vehicles Detection With Area Based on Image Segmentation). Jurnal Transformatika, 9(2), 55–63.
