【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。要步驟，定位的準(zhǔn)確與否直接影響車(chē)牌識(shí)別率。理、車(chē)牌粗定位和精定位的方法。本次設(shè)計(jì)采取的是基于微分的邊緣檢測(cè)，進(jìn)行處理，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。KEYWORDS：imageacquisition，imagepreprocessing，edgedetection，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。

　　

【正文】 河南科技大學(xué)本科畢業(yè)設(shè)計(jì)（論文） 36 致 謝 短暫的大學(xué)生活就要結(jié)束了，在此，感謝所有在學(xué)習(xí)和生活中給 予我關(guān)心和幫助的人們。 首先我要感謝我的導(dǎo)師和同組成員，本系畢業(yè)設(shè)計(jì)的選題、課題調(diào)研與撰寫(xiě)工作實(shí)在和老師的直接關(guān)懷和同組成員配合下完成，老師淵博的知識(shí)、嚴(yán)謹(jǐn)?shù)闹螌W(xué)態(tài)度、一絲不茍的工作作風(fēng)、和不厭其煩的精神對(duì)我影響至深，使我受益終生，在此我向和老師表示崇高的敬意和衷心的感謝。 其次，在我的大學(xué)期間，任課老師和同學(xué)都給予了我熱情的幫助和無(wú)私的指導(dǎo)，在此想這些辛勤的老師們表示衷心的感謝。 與此同時(shí)，我還得到了很多其他專(zhuān)業(yè)同學(xué)的幫助，在此，向所有給予我?guī)椭呐笥褌儽硎局孕牡母兄x。 最后，向所有曾給予作者關(guān)心和幫助的 老師和同學(xué)們?cè)俅伪硎咀钪孕牡母兄x，向參加論文評(píng)審、答辯的專(zhuān)家和老師表示衷心的感謝和崇高的敬意。 河南科技大學(xué)本科畢業(yè)設(shè)計(jì)（論文） 37 英文資料翻譯 Image processing is not a one step process． We are able to distinguish between several steps which must be performed one after the other until we can extract the data of interest from the observed scene． In this way a hierarchical processing scheme is built up as sketched in Fig． The figure gives an overview of the different phases of image processing. Image processing begins with the capture of an image with a suitable， not necessarily optical， acquisition system． In a technical or scientific application，we may choose to select an appropriate imaging system． Furthermore， we can set up the illumination system， choose the best wavelength range， and select other options to capture the object feature of interest in the best way in an image． Once the image is sensed， it must be brought into a form that can be treated with digital process is called digitization. With the problems of traffic are more and more serious. Thus Intelligent Transport System (ITS) es out. The subject of the automatic recognition of license plate is one of the most significant subjects that are improved from the connection of puter vision and pattern recognition. The image imputed to the puter is disposed and analyzed in order to localization the position and recognition the characters on the license plate express these characters in text string form The license plate recognition system (LPSR) has important application in ITS. In LPSR, the first step is for locating the license plate in the captured image which is very important for character recognition. The recognition correction rate of license plate is governed by accurate degree of license plate location. In this paper, several of methods in image manipulation are pared and analyzed, then e out the resolutions for localization of the car plate. The experiences show that the good result has been got with these methods. The methods based on edge map and frequency analysis is used in the process of the localization of the license plate, that is to say, extracting the 河南科技大學(xué)本科畢業(yè)設(shè)計(jì)（論文） 38 characteristics of the license plate in the car images after being checked up for the edge, and then analyzing and processing until the probably 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 河南科技大學(xué)本科畢業(yè)設(shè)計(jì)（論文） 39 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 a