An Ensemble Approach for Moving Vehicle Detection and Tracking by Using Ni Vision Module

Abstract

In the recent years, surveillance systems and video monitoring have been largely used for the management of traffic. Acquired images and video clips from the road traffic can be utilized in the Lab VIEW program environment. LabVIEW Vision Assistant is focusing on to discover the moving vehicles. This approach finds a formation of resemblance in the frames for vehicle and non-vehicle objects, while the vehicles tracking progress through image sequences. For improving the adaptive background mixture model, there is indeed of background subtraction method. In addition, it constructs the system more precisely with rapid learning also. Therefore, its performance shows the adaptability on the occurrence of any real time videos. This evolve system robustly detect the vehicles on resolving the background objects which help to track the vehicles effectively. The various types of attributes related to moving vehicles are extracted which are used in feature extraction techniques for tracking the vehicles. The extracted features utilize in the module of LabVIEW environment and Vision Assistant module works mainly in the detection of moving vehicles objects. This proposed work can help in reducing the cost of traffic monitoring systems and real automation of traffic observation systems.