Study On The Traffic Information Collection And Detection System Based On Line-CCD Camera

Adopting advanced techniques in electronics,automation,computer and digitalcommunication,etc.,the Intelligent Transportation System,i.e.ITS,represents the novelgeneration of traffic information managing and controlling system,which can provide trafficinformation of volume of vehicles or state of roads in time,keep records of traffic irregularity,enhance ability of sudden traffic accidents,promote traffic safety & efficiency together withconvenient services for public travels and better improvements of environmental quality andtherefore advances national traffic transportation cause greatly.As one of essential parts in ITS,the real-time collection of road traffic information playsa vital role in ITS information collection.It is a necessary premise to obtain various trafficparameters timely and precisely and level of road traffic detectors and correspondingdetecting techniques have direct effect on management or running level of the whole roadtraffic system.With the maturity of all-sided vehicle surveillance and detection techniquesbased on image analysis and computer vision,development of traffic detection was alsochanged from observation of traffic phenomena and traffic signal controlling manually towhich based on video detection.Vehicle detection based on video method could detect themain traffic parameter of traffic volume completely by means of video vehicle tracking,control traffic signal automatically,and alarm with dangerous occurrence.It is undoubtedly amost lively traffic information collection method with deep potential.This thesis has performed some researches on several vital techniques of trafficparameters detecting system based on line-CCD camera.It emphasizes on detailed discussionabout the important and basic issues under traffic scenes such as background extraction,videovehicle detection and tracking,plate recognition,realization of traffic surveillance system anddata stream simulation etc.For these problems,some deep viewpoints or actual realizationmeans is presented and necessary test and simulation is performed.In detail,the main research work finished in the thesis can be summarized as follows:1.A background extraction method based on wavelet transformation and an improvedmethod for Otsu threshold are presented.Combining the feature of wavelet transformation,abackground extraction method is presented based on image from line-CCD camera.Theexperimental results show that the proposed method can effectively polish the noise from lamp and extract the background.At the same time,background extracted is depended on thethreshold election.And the average of image grey represents the distributing of it.So,theimproved Otsu threshold method that the average is instead of variance is presented.The realexperimental results show that the improved Otsu threshold method can effectively extract thebackground.2.An external force field for active contour model-PMF is presented.ThePerona-Malik model which is a classical method of anisotropic removing noises has theadvantage of remaining the edge map of image.The negative gradient of restored image byPerona-Malik model is defined as external forces,and the segmentation results that it affectson active contour model are studied.Accordingly,an external force field for active contourmodel-PMF is presented.Theoretical analyses and experimental results show that PMF canretain the edge information of image and enter into the edge's concaves entirely.In the meantime,PMF has large capture range with few restrictions to initial curves.Moreover,becausePMF is derived from Perona-Malik,it is robust to the noise.3.A traffic match method based on iterative weight is presented,which can efficientlydiscard the outliers.Now,most of match method is base on least mean-square method.Whenthe noise is gaussian distribution,the solution based on least mean-square method is best.But,when the outliers appear,and the outliers are regard as the gaussian noise,which maybe resultin error solution.So,the outliers should be discarded.The weight of each point is determinedbased on the inverse of error and the error is obtained based on the weight.After severaliterations,the weights of the outliers trend to zero and the match result is obtained with goodaccuracy.The method can overcome the disadvantages of both the least-squares method andthe Random Sample and Consensus method.The theory and experiments with both simulateand real data demonstrate that the method is very efficient and robust.4.A new image enhancement method for car license plate recognition is presented.Segmentation of license plate region is a key procedure in a car license plate recognitionsystem,enhancing the plate region of the captured image and suppressing the backgroundarea can effectively reduce the difficulty of the plate segmentation task.In this paper,theimage used for license recognition is decomposed into a group of binary versions,and thenconnected regions in the binary images are labeled and their feature parameters are calculated.As the connected regions in the plate area and those in the background are very different in the calculated feature parameters,so the connected regions which likely belong to the platearea can be preserved and the others can be erased.A new image with plate region enhancedcan be reconstructed from the processed binary images.In order to reduce the computationload and make the method realizable,contour lines instead of connected component labelingis used in the paper to describe the connected regions.The experimental results show that theproposed method effectively enhances the plate area and suppress the background area,improves the plate segmentation performance.The new method can be well applied in the realcar license plate recognition systems.5.Traffic information is the key and foundation of traffic management and programming.the real-time collection of road traffic information,detection the traffic affairs and processionand application these information and affairs play an important role on improving theefficiency of traffic system,the decrease of traffic accident,increase the ability of solving theemergency affairs and optimization of programming design.To obtain traffic information,atraffic information collection and detection system based on line-CCD camera is presented.The system consists of data and image library,vidio trigger,image capture,sectioncalculagraph,parameter obtaining,plate recognition,etc.And the system can detect the trafficvelocity and flux,recognise plate,recode traffic.At the same time,the method for vehicle andits velocity detection is presented and applied to the system.The experiment results show thatthe system can accurately detect the traffic and its velocity.