Pengenalan Plat Nomor Mobil Menggunakan Metode Learning Vector Quantization - Beryl Labique Ahmadie; Agus Wahyu Widodo; Fitri Utaminingrum (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2018)
The amount of vehicles in Indonesia increases every year, this causing long queues at gates, mall, or tolls that require the process of recording license plates. This research will help simplify the process of recording license plate by creating a vehicle license plate recognition system. The system will try to recognize the license plate from a digital image. The first step in the license plate recognition system is to detect the location of the license plate by applying vertical edge detection because the area of license plate contains rich edge and texture information. The next step is character segmentation, this is a process to get characters from license plate image. this can be done by applying connected component algorithm. The last step is character recognition using learning vector quantization algorithm. Based on the result of this research, the highest accuracy is 94% in the license plate detection process, the highest f-measure value is 0,88 in the character segmentation process and the highest accuracy for character recognition using Learning Vector Quantization algorithm is 86,67%.