Research on vehicle counting and statistics function in monitoring videos based on OpenCV-python
In response to the pressing need for the acquisition of real-time traffic flow monitoring information in surveillance videos,this study explored a vehicle counting and statistical analysis function by using OpenCV-Python.Firstly,it employed a foreground extraction algorithm based on background subtraction to segment vehicles within the images.Then,it processed and filtered vehicles through contour detection and morphological operations to eliminate noise and unnecessary detection results so as to ensuring accurate counting.Finally,it conducted comparative study on this approach and the approach based on the combination of the YOLOv5 model and the SORT algorithm.Experimental results indicated that both approaches can effectively count vehicles.However,traditional image processing lacks high precision of deep learning and is difficult to adapt to different road scenarios.Therefore,it is recommended to combine traditional image processing with deep learning to provide a better solution for vehicle counting.
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