• Sennappan S
• Mrs. K.Mahalakshmi
• Somesh M S
• Manikandan A

Real-time vehicle recognition, tracking, and counting are of tremendous interest to researchers and are required by society at large for convenient, easy, and secure vehicle movements in cities. We suggest a vehicle count detection, tracking, and discovery technique for video image processing. We convert the RGB video frame into the HSV colour space, which makes it easier to distinguish the colours of the automobiles. Each frame is cleaned of noise. Vehicle detection is solely based on color-related characteristics of the vehicles. Kalman filter is used for vehicle tracking together with data association. It is decided how many cars are running in a certain lane or in a movie. We suggest an innovative approach to identifying, following, and counting the vehicles on a road. OpenCV has been used to implement it on the Raspberry Pi 3. The suggested methodology outperforms the rear-view vehicle recognition and tracking method (Bin et al., 2014) and the morphological operation method (Zezhong et al., 2013) in terms of vehicle detection accuracy and cost, according to our comparison of their respective results.

"A NOVEL APPROACH IN REAL-TIME VEHICLE DETECTION AND TRACKING USING RASPBERRY PI ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.i814-i818, May-2023, Available :http://www.jetir.org/papers/JETIR2305931.pdf

"A NOVEL APPROACH IN REAL-TIME VEHICLE DETECTION AND TRACKING USING RASPBERRY PI ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppi814-i818, May-2023, Available at : http://www.jetir.org/papers/JETIR2305931.pdf