The invention relates to an expressway illegal parking detection method based on
kernel density estimation and belongs to the field of
image processing. The expressway illegal parking detection method comprises the following steps: firstly, carrying out background extraction by adopting a non-parameter kernel
density model to obtain a
background image; secondly, updating the
background image by adopting a gradually-changed updating manner to obtain an updated
background image; removing the background image from a currently acquired image to obtain a movement foreground; thirdly, calibrating positions of
mass centers of a movable target vehicle; then tracking the target vehicle and measuring the distance between the
mass centers; when the distance between the
mass centers is gradually reduced, representing that the target vehicle enters a
speed reduction process; after the target vehicle enters the
speed reduction process, judging a movement state of the target vehicle; when the movement state is a static state, calculating illegal parking time; finally, determining whether the target vehicle is illegally parked or not according to the illegal parking time. The expressway illegal parking detection method provided by the invention can be used for monitoring a monitored scene in real time and alarming in time when the vehicle is illegally parked; the
processing speed is rapid and the accuracy of alarming is improved; the expressway illegal parking detection method has the characteristics of good instantaneity, high robustness, high accuracy and the like.