Detecting Vehicle Numbers Using Google Lens-Based ESP32CAM to Read Number Characters

Tukino Paryono (Universitas Buana Perjuangan, Karawang, Indonesia)
Ahmad Fauzi (Universitas Buana Perjuangan, Karawang, Indonesia)
Rizki Aulia Nanda (Teknik Mesin, Fakultas Teknik, Universitas Buana Perjuangan Karawang)
Saepul Aripiyanto (Fakultas Teknik Informatika UIN Jakarta, Jakarta)
Muhammad Khaerudin (Teknik Informatika, Universitas Bhayangkara Jakarta Raya, Jakarta)

MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer
Vol 22 No 3 (2023)

plates continues to increase. This research aimed to detect vehicle license plates using ESP32CAM and utilize photo text reading using Google Lens, which can be used online to retrieve numeric characters. The method approach was to connect Wifi connectivity to the ESP32CAM, which had been programmed to detect vehicle plates. Vehicle plates that have been detected and recognized were inputted into Google Lens to capture the resulting text from the ESP32CAM camera recording. The results of this study were that for 70 seconds, ten plate samples were obtained, which were 100% perfect in reading license plates on Google Lens, namely six plates and two plates read 90%, one plate read 60%, and one plate read 0%. The research conclusions obtained were ten samples, six samples with perfect readings, and one error sample because of the white plate color. Thus, the main objective was to obtain the results of the vehicle plate detection and retrieve the text from the recording results