Kanishkha L. D., Poojah G., Edna Elizabeth N.
Stolen Car Detection Using Image Processing and Machine Learning
In recent years, vehicular stealing has been steadily increasing around the world. Existing theft control methods to find stolen vehicles are inadequate in this current scenario. Thus, the motive of our project is to explore image processing and machine learning techniques to find an effective method to detect vehicles and extract registration numbers. We aim to capture frames only when there is a motion, then run the License Plate Recognition (LPR) algorithm, thereby reducing computational complexity. Once the license plate is detected by comparing it with the records of the stolen car, the owner of the car is intimated with the location of the marked vehicle using the Global Positioning System (GPS) of the cameras.
Image processing, machine learning, LPR, neural network
Cite this paper
Kanishkha L. D., Poojah G., Edna Elizabeth N.. (2022) Stolen Car Detection Using Image Processing and Machine Learning. International Journal of Signal Processing, 7, 48-52