Design And Research Of Detection System About Illegal Barge

The drone is equipped with a high-definition camera,which can perform tasks such as marine oil spill emergency monitoring,ship search,ship in distress and personnel positioning,and marine sovereign inspection.This paper aims to develop a detection system about illegal barge,which can detect the illegal barge in real time during the patrol process of the drone,and realize the target identification,positioning and detection,which can greatly improve the work experience of the staff and improve the work efficiency.In this paper,we have designed a system for detecting illegal barge,which can greatly save manpower and material resources and improve work efficiency.The system includes two parts: real-time detection and video processing.At the same time,the system can not only detect targets under normal weather,but also detect targets better in foggy weather.The quality of the aerial image of the drone is easily affected by the haze weather,resulting in blurred images,which has a great impact on the subsequent processing of the image.Therefore,in this study,the defogging and target detection algorithms are the key to the system.In this paper,a new image method about dehazing is proposed for single image.This method combines Network-in-Network with MSCNN(Single Image Dehazing via Multi-Scale Convolutional Neural Networks)to estimate the transmission map.In the test stage,we estimate the transmission map of the input hazy image based on the trained model,and then generate the dehazed image using the estimated atmospheric light and computed transmission map.Extensive experiments have shown that the proposed algorithm overperformance traditional methods.After the defogging is completed,the image after the defogging is detected by the target detection algorithm,thereby realizing the detection of the illegal barge.