Moving Vehicle Detection Level Set Extraction

Motion object detection, extraction and traffic flow statistics is a hotresearch in image domain of computer, and has very important applicationvalues. As the most worthy of study content, image processing technology isthe realization of motion detection and flow statistics is an effective method,it has aroused the extensive attention of researchers.In this paper, the common methods of target detection are analyzed, amotion object extraction algorithm based on level set C-V model is proposedin view of the traditional frame difference method in light, weather changesapparent inelasticity: firstly, on the moving area in initial detection, framedifference algorithm was improved and adjacent moving object pixels incurrent image were detected through adaptive threshold and adjacent videoframe subtracting technique. The proposed approach can improve the changeof light and weather effective; secondly, Construct and realize the level setC-V model of extracting the moving object contour though being processedby morphology after motion object detection. Experimental results show thatthe proposed approach for extracting moving object, which edge anddetecting accuracy rate is more powerful and can effectively extract themoving object.Based on the above method to detect moving vehicles, multi-lane testline traffic flow statistics method was improved. It uses a single virtualdetection line technology to realize traffic flow statistics of multi lane, andimprove the cross road traffic flow statistics effectively. As an experiment,develop a traffic flow statistics system, this system divided into four modules,which are video load module, virtual detecting line set module, video controlmodule, traffic flow statistics module. Experimental results show that theproposed method has the following characteristics: the real-time property andhigh recognize rate.