Naslov
System for automatic detection and classification of cars in traffic

Autori
Bralić, Niko ; Musić, Josip

Izvornik
St open (2718-3734) 3 (2022); E2022.2102.11., 31

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
object detection ; CNN ; YOLO ; SSD ; kNN ; Raspberry Pi

Sažetak
Objective: To develop a system for automatic detection and classification of cars in traffic in the form of a device for au-tonomic, real-time car detection, license plate recognition, and car color, model, and make identification from video. Methods: Cars were detected using the You Only Look Once (YOLO) v4 detector. The YOLO output was then used for clas-sification in the next step. Colors were classified using the k-Nearest Neighbors (kNN) algorithm, whereas car models and makes were identified with a single-shot detector (SSD). Finally, license plates were detected using the OpenCV li-brary and Tesseract-based optical character recognition. For the sake of simplicity and speed, the subsystems were run on an embedded Raspberry Pi computer. Results: A camera was mounted on the inside of the wind-shield to monitor cars in front of the camera. The system processed the camera’s video feed and provided informa-tion on the color, license plate, make, and model of the ob-served car. Knowing the license plate number provides ac- cess to details about the car owner, roadworthiness, car or license place reports missing, as well as whether the license plate matches the car. Car details were saved to file and dis-played on the screen. The system was tested on real-time images and videos. The accuracies of car detection and car model classification (using 8 classes) in images were 88.5% and 78.5%, respectively. The accuracies of color detection and full license plate recognition were 71.5% and 51.5%, respectively. The system operated at 1 frame per second (1 fps). Conclusion: These results show that running standard machine learning algorithms on low- cost hardware may enable the automatic detection and classification of cars in traffic. However, there is significant room for improve-ment, primarily in license plate recognition. Accordingly, potential improvements in the future development of the system are proposed.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

POVEZANOST RADA