Developing and validating a real time video based traffic counting and classification

An algorithm program was developed to detect vehicles in traffic videos and get the vehicle count for the small time period as a tool that can assist researchers who seek vehicle counting. This system approach has been presented for extracting traffic data using video image processing. Meanwhile, an offline program focuses on extracting vehicles, tracking them and providing the vehicle count for a short period of time. It uses background subtraction, shadow removal, and pixel analysis for extracting moving objects. The results show that the algorithm is capable of counting 95% of the vehicles due to some shaking in the video feed. These data have been analysed by the paired samples t-test to show the credibility of the results which have been approved to be useful according to the values of correlation and P-value compared with the values of the observation method. Also, the classification of vehicles was performed using the improfile command in Matlab-Video Image Processing that computes the colours intensity values along a line or a multiline path in an image