Target detection system for communication engineering project

Abstract

The invention discloses a target detection system for a communication engineering project. Thetarget detection system comprises a cloud computing module, an acquisition module, an image preprocessing module, a target detection module, an image transmission module and a control center module; the system acquires an image set of a moving target through the acquisition module, and an environment analysis module acquires environment data and analyzes the environment data to obtain influence factors; the correlation analysis module and the cloud computing module detect the image by using the influence factors and R-FCN and YOLO target detection algorithms to obtain a first-class target detection result and a second-class target detection result, and the control center module analyzes the first-class target detection result and the second-class target detection result to obtain a final target detection result. According to the system, the requirement for the bandwidth of image transmission is lowered, the defect that a YOLO algorithm detects a tiny target is overcome through the combination of the two target detection algorithms, and the real-time performance and accuracy of target detection are improved.

Description

technical field [0001] The invention relates to the technical field of target detection, in particular to a target detection system for communication engineering projects. Background technique [0002] Target detection is a very important research problem in the field of computer vision. One of its main tasks is to accurately identify and locate the target in the image. Target detection has a wide range of applications in various fields. In the field of communication technology due to Massive data transmission makes the network bandwidth resources insufficient, which poses a major challenge to the data processing mode; the target detection algorithm can detect the dynamic target in the surveillance video, such as face recognition technology, vehicle detection technology, but due to the existence of Due to the influence of illumination changes, shadows, noise interference, camera shake, and bad weather factors, the images of moving targets in surveillance videos may become bl...

AI Technical Summary

Problems solved by technology

[0002] Target detection is a very important research problem in the field of computer vision. One of its main tasks is to accurately identify and locate the target in the image. Target detection has a wide range of applications in various fields. In the field of communication technology due to Massive data transmission makes the network bandwidth resources insufficient, which poses a major challenge to the data processing mode; the target detection algorithm can detect the dynamic target in the surveillance video, such as face recognition technology, vehicle detection technology, but due to the existence of Due to the influence of illumination changes, shadows, noise interference, camera shake, and bad weather factors, the images of moving targets in surveillance videos may become blurred or even tiny targets are blocked. Although there are many complex target detection methods in the prior art Algorithm, R-FCN technology can detect tiny targets, but because the target detection algorithm is too complex, resulting in slow detection speed, YOLO technology can greatly improve the target detection speed, but it will ignore the detection of tiny targets, in order to adapt to complex and changeable The application environment can improve the real-time performance and accuracy of the target detection process, and can greatly reduce the demand for network bandwidth resources for mass data transmission. The invention provides a target detection system for communication engineering projects

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