【導(dǎo)讀】智能交通領(lǐng)域應(yīng)用的重要研究課題之一。在車(chē)牌自動(dòng)識(shí)別系統(tǒng)中，首先要將車(chē)牌。直接影響車(chē)牌識(shí)別率。MATLAB的車(chē)牌識(shí)別系統(tǒng)，通過(guò)編寫(xiě)M文件，對(duì)各種車(chē)輛。圖像處理方法進(jìn)行分析、比較,提出了車(chē)牌預(yù)處理、車(chē)牌粗定位和精定位的方法。處理，從而得到車(chē)牌的精確區(qū)域并且取得了較好的定位結(jié)果。隨著交通問(wèn)題的日益嚴(yán)重，智能交通系統(tǒng)應(yīng)運(yùn)而生。本的形式顯示出來(lái)。園區(qū)車(chē)輛管理、停車(chē)場(chǎng)管理有著特別重要的應(yīng)用價(jià)值，受到業(yè)內(nèi)人士的普遍關(guān)注。由于在現(xiàn)實(shí)中，汽車(chē)的車(chē)牌圖像受到光照、背景、車(chē)型。等外界干擾因素以及拍攝角度、遠(yuǎn)近等人為因素的影響，造成圖像受光不均勻，車(chē)牌區(qū)域不明顯，給車(chē)牌區(qū)域的提取帶來(lái)了較大的困難。成為必然的趨勢(shì)，交通管理自動(dòng)化越來(lái)越成為亟待解決的問(wèn)題。理汽車(chē)圖像，自動(dòng)識(shí)別汽車(chē)牌號(hào)。

　　

【正文】 s used in the process of the localization of the license plate, that is to say , extracting the characteristics of the license plate in the car images after being checked up for the edge, and then analyzing and processing until theprobably area of license plate is extracted. The automated license plate location is a part of the image processing ,it’ s also an important part in the intelligent traffic system． It is the key step in the Vehicle License Plate Recognition LPR .A method for the recognition of images of different backgrounds and different illuminations is proposed in the upper and lower borders are determined through the gray variation regulation of the character left and right borders are determined through the blackwhite variation of the pixels in every row. The first steps of digital processing may include a number of different operations and are known as image processing． If the sensor has nonlinear characteristics， these? need to be corrected． Likewise，brightness and contrast of the image may require improvement． Commonly，too ， coordinate transformations are needed to restore geometrical distortions introduced during image formation． Radiometric and geometric corrections are elementary pixel processing operations． It may be necessary to correct known disturbances in the image， for instance caused by a defocused optics， motion blur， errors in the sensor，or errors in the transmission of image signals． We also deal with reconstruction techniques which are required with many indirect imaging techniques such as tomography that deliver no direct image． A whole chain of processing steps is necessary to analyze and identify objects． First， adequate filtering procedures must be applied in order to distinguish the objects of interest from other objects and the background． Essentially， from an image（ or several images）， one or more feature images are extracted． The basic tools for this task are averaging and edge detection and the analysis of simple neighborhoods and plex patterns known as texture in image processing． An important feature of an object is also its motion． Techniques to detect and determine motion are necessary． Then the object has to be separated from the background． This means that regions of constant features and discontinuities must be identified． This process leads to a label image． Now that we know the exact geometrical shape of the object， we can extract further information such as the mean gray value， the area， perimeter， and other parameters for the form of the object[3] ． These parameters can be used to classify objects ． This is an important step in many applications of image processing， as the following examples show： In a satellite image showing an agricultural area， we would like to distinguish fields with different fruits and obtain parameters to estimate their ripeness or to detect damage by parasites． There are many medical applications where the essential problem is to detect pathologial changes． A classic example is the analysis of aberrations in chromosomes ． Character recognition in printed and handwritten text is another example which has been studied since image processing began and still poses significant difficulties． You hopefully do more， namely try to understand the meaning of what you are reading． This is also the final step of image processing， where one aims to understand the observed scene． We perform this task more or less unconsciously whenever we use our visual system． We recognize people，we can easily distinguish between the image of a scientific lab and that of a living room， and we watch the traffic to cross a street safely． We all do this without knowing how the visual system works． For some times now， image processing and putergraphics have been treated as two different areas． Knowledge in both areas has increased considerably and more plex problems can now be treated． Computer graphics is striving to achieve photorealistic putergenerated images of threedimensional scenes ， while image processing is trying to reconstruct one from an image actually taken with a camera． In this sense，image processing performs the inverse procedure to that of puter graphics． We start with knowledge of the shape and features of an object―at the bottom of Fig. and work upwards until we get a twodimensional image． To handle image processing or puter graphics， we basically have to work from the same knowledge． We need to know the interaction between illumination and objects， how a threedimensional scene is projected onto an image plane， etc． There are still quite a few differences between an image processing and a graphics workstation． But we can envisage that， when the similarities and interrelations between putergraphics and image processing are better understood and the proper hardware is developed， we will see some kind of generalpurpose workstation in the future which can handle puter graphics as well as image processing tasks[5]． The advent of multimedia， i. e. ， the integration of text， images， sound， and movies，will further accelerate the unification of puter graphics and image processing． In January 1980 Scientific American published a remarkable image called Plume 2， the second of eight volcanic eruptions detected on the Jovian moon by the spacecraft Voyager 1 on 5 March 1979． The picture was a landmark image in interplaary exploration ― the first time an erupting volcano had been seen in space． It was also a triumph for image processing． Satellite imagery and images from interplaary explorers have until fairly recently been the major users of image processing techniques，where a puter image is numerically manipulated to produce some desired effectsuch as making a particular aspect or feature in the image more visible． Image processing has its roots in photo reconn