Application of Neural Network in Image Detection of Illegal Billboards
Xue-Hong Jiang, Hui-Li Feng, Yijie Dong · 2020
In recent years, urban management is gradually developing towards informationization.There are corresponding processing mechanisms for illegal billboards and illegal parking in urban management, but the method of detecting illegal billboards based on machine vision is still under study.At present, the automatic detection method of illegal billboards based on machine vision is generally carried out under ideal conditions, and the experiment is carried out under a simple background.This paper takes a street in Hebei Province as the research object, and studies the illegal billboard area under natural conditions, and proposes to use the machine vision-based method to automatically detect the illegal billboards.In the surveillance image, according to the street scene detected by the computer.Image information enables status evaluation of billboard placement.The detection algorithm of this paper uses the multi-angle suggestion area to accurately locate the illegal billboards in the image, and mark the detected billboards.Compared with the direct detection of the billboard in the image, the interference of the background factor on the target area is removed, and the false detection rate is effectively reduced.In billboard detection, this paper proposes an improved region suggestion algorithm to generate higher quality candidate regions in an image for adapting to billboards of various poses under natural conditions.Experimental data shows that the algorithm has good adaptability to the detection of billboards in surveillance images.