Research And Design On Automatic Capture System Of Vehicles Illegal Parking

In recent years,with the development of economy and science and technology,the scale of motor vehicles and traffic flow increase year by year,and the improvement of the management level of highway and urban traffic is imperative.Highway development and motor vehicle management system gradually improve,the urban traffic management system into practical applications provide an important opportunity,this paper illegally parked vehicles automatically capture system design and implementation,Automatic Capture System of Vehicles Illegal Parking mainly consists of several modules: Contrary to stop judgment,automatic capture,license plate location,character recognition.Automatic Capture System of Vehicles Illegal Parking is in this context for the realization of the system can realize automatic and real-time monitoring and illegally parked vehicles,license plate location,character recognition,system using advanced communication and computer technology,control technology from the monitoring equipment to obtain illegally parked vehicles in video image information.In this paper,we study the automatic Capture System of Vehicles Illegal Parking,the system based on image processing technique,mathematical morphology,pattern recognition and so on,needle for a variety of situations of license plate image for recognition and location,can be used in most vehicle management situations.Automatic Capture System of Vehicles Illegal Parking with traditional vehicles illegally parked management method compared,it can improve the work efficiency,can save the human,material and financial resources,illegally parked vehicles automatically capture system,realizes the management of vehicle intelligent,scientific,standardization,secure development of urban road traffic.Therefore,automatic Capture System of Vehicles Illegal Parking has a wide application prospect.Automatic Capture System of Vehicles Illegal Parking is in this context for the realization of the system can realize automatic monitoring and illegally parked vehicles,license plate location and character recognition three parts,this paper the in turn for the systematic study.The three part introduces the following vehicles illegally parked automatic capture system structure:One,contrary to stop judgment: the effective detection of the object is to achieve the movement is to achieve the basis for judging the vehicle violation.In this paper,the background subtraction method is used to determine the vehicle violation stop signs.The principle is that the background is represented by a special model,and then the detection of moving objects is realized by using the difference between the background and the image.In this paper,the background of the complex urban traffic scene is obtained by using the adaptive mixed Gauss model.Two,automatic capture: automatic capture module based on the judgment of illegally parked for the true,start high-definition camera,will save the file in a fixed format,for subsequent processing.Three,license plate location: Research on the image segmentation,preprocessing operation,license plate area feature analysis,license plate location algorithm and so on.Four,character recognition: license plate location is the precondition of character recognition,character recognition operation mainly includes: image preprocessing,character segmentation,BP neural network for character recognition.Experimental results show that,automatic Capture System of Vehicles Illegal Parking can locate license plate,character segmentation and automatic identification,system performance good and stable.Thus,the organic combination of a variety of pre processing and pattern recognition technology to improve the system of automatic recognition performance,automatic Capture System of Vehicles Illegal Parking adhere to the principle of effective and practical,is using BP neural network and artificial intelligence technology combined with the realization of the system,they will become an important development trend in the research field of pattern recognition.