圖像處理外文翻譯

1、<p><b>　　英文資料翻譯</b></p><p>　　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

2、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.</p><p>　　Image

3、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

4、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

5、can be treated with digital computers.This process is </p><p>　　With the problems of traffic are more and more serious. Thus Intelligent Transport System (ITS) comes out. The subject of the automatic recogni

6、tion of license plate is one of the most significant subjects that are improved from the connection of computer vision and pattern recognition. The image imputed to the computer is disposed and analyzed in order to local

7、ization the position and recognition the characters on the license plate express these characters in text string form The license plate r</p><p>　　The automated license plate location is a part of the image

8、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 ill

9、uminations is proposed in the paper.the upper and lower borders are determined through the gray variation regulation of the character distribution.The left and right borders are determined through the black-white variati

10、</p><p>　　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．Li

11、kewise，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 correc

12、tions are elementary pixel processing operations．</p><p>　　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

13、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.</p><p>　　A whole cha

14、in 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，fr

15、om 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 complex patterns known as texture in ima

16、ge processing．An important feature of an object i</p><p>　　There are many medical applications where the essential problem is to detect pathologi-al changes．A classic example is the analysis of aberrations i

17、n chromosomes．Character recognition in printed and handwritten text is another example which has been studied since image processing began and still poses significant difficulties．</p><p>　　You hopefully do

18、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 w

19、e 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 t

20、he visual system works．For some times now，i</p><p>　　There are still quite a few differences between an image processing and a graphics workstation．But we can envisage that，when the similarities and interrel

21、ations between computergraphics and image processing are better understood and the proper hardware is developed，we will see some kind of general-purpose workstation in the future which can handle computer graphics as wel

22、l as image processing tasks[5]．The advent of multimedia，i. e. ，the integration of text，images，sound，and movies，will further ac</p><p>　　In January 1980 Scientific American published a remarkable image called

23、 Plume2，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 interplanetary exploration—the first time an erupting volcano had

24、 been seen in space．It was also a triumph for image processing．</p><p>　　Satellite imagery and images from interplanetary explorers have until fairly recently been the major users of image processing techniq

25、ues，where a computer image is numerically manipulated to produce some desired effect-such as making a particular aspect or feature in the image more visible.</p><p>　　Image processing has its roots in photo

26、reconnaissance in the Second World War where processing operations were optical and interpretation operations were performed by humans who undertook such tasks as quantifying the effect of bombing raids．With the advent o

27、f satellite imagery in the late 1960s，much computer-based work began and the color composite satellite images，sometimes startlingly beautiful, have become part of our visual culture and the perception of our planet．</

28、p><p>　　Like computer graphics，it was until recently confined to research laboratories which could afford the expensive image processing computers that could cope with the substantial processing overheads requi

29、red to process large numbers of high-resolution images．With the advent of cheap powerful computers and image collection devices like digital cameras and scanners，we have seen a migration of image processing techniques in

30、to the public domain．Classical image processing techniques are routinely emplo</p><p>　　A recent mainstream application of image processing is the compression of images—either for transmission across the Int

31、ernet or the compression of moving video images in video telephony and video conferencing．Video telephony is one of the current crossover areas that employ both computer graphics and classical image processing techniques

32、 to try to achieve very high compression rates．All this is part of an inexorable trend towards the digital representation of images．Indeed that most powerful ima</p><p>　　Image processing is characterized by

33、 a large number of algorithms that are specific solutions to specific problems．Some are mathematical or context-independent operations that are applied to each and every pixel．For example，we can use Fourier transforms to

34、 perform image filtering operations．Others are“algorithmic”—we may use a complicated recursive strategy to find those pixels that constitute the edges in an image．</p><p>　　Image processing operations often

35、form part of a computer vision system．The input image may be filtered to highlight or reveal edges prior to a shape detection usually known as low-level operations．In computer graphics filtering operations are used exten

36、sively to avoid abasing or sampling artifacts．</p><p><b>　　中文翻譯</b></p><p>　　圖像處理不是一步就能完成的過(guò)程?？蓪⑺殖芍T多步驟，必須一個(gè)接一個(gè)地執(zhí)行這些步驟，直到從被觀察的景物中提取出有用的數(shù)據(jù)。依據(jù)這種方法，一個(gè)層次化的處理方案如圖12-1所示，該圖給出了圖像處理不同階段的概觀。&l

37、t;/p><p>　　圖像處理首先是以適當(dāng)?shù)牡灰欢ㄊ枪鈱W(xué)的采集系統(tǒng)對(duì)圖像進(jìn)行采集。在技術(shù)或科學(xué)應(yīng)用中，可以選擇一個(gè)適當(dāng)?shù)某上裣到y(tǒng)。此外，可以建立照明系統(tǒng)，選擇最佳波長(zhǎng)范圍，以及選擇其他方案以便用最好的方法在圖像中獲取有用的對(duì)象特征。一旦圖像被檢測(cè)到，必須將其變成數(shù)字計(jì)算機(jī)可處理的形式，這個(gè)過(guò)程稱之為數(shù)字化。</p><p>　　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。汽車牌照自動(dòng)識(shí)別系

38、統(tǒng)是近幾年發(fā)展起來(lái)的計(jì)算機(jī)視覺(jué)和模式識(shí)別技術(shù)在智能交通領(lǐng)域應(yīng)用的重要研究課題之一。課題的目的是對(duì)攝像頭獲取的汽車圖像進(jìn)行預(yù)處理,確定車牌位置,提取車牌上的字符串，并對(duì)這些字符進(jìn)行識(shí)別處理,用文本的形式顯示出來(lái)。車牌自動(dòng)識(shí)別技術(shù)在智能交通系統(tǒng)中具有重要的應(yīng)用價(jià)值。在車牌自動(dòng)識(shí)別系統(tǒng)中，首先要將車牌從所獲取的圖像中分割出來(lái)，這是進(jìn)行車牌字符識(shí)別的重要步驟，定位準(zhǔn)確與否直接影響車牌識(shí)別率。本文在對(duì)各種車輛圖像處理方法進(jìn)行分析、比較的基礎(chǔ)上,提

39、出了車牌預(yù)處理、車牌粗定位和精定位的方法，并且取得了較好的定位結(jié)果。車牌定位采取的是邊緣檢測(cè)的頻率分析法。從經(jīng)過(guò)邊緣提取后的車輛圖像中提取車牌特征,進(jìn)行分析處理,從而初步定出車牌的區(qū)域，再利用車牌的先驗(yàn)知識(shí)和分布特征對(duì)車牌區(qū)域二值化圖像進(jìn)行處理，從而得到車牌的精確區(qū)域。</p><p>　　汽車牌照的自動(dòng)定位是圖像處理的一種，也是智能交通系統(tǒng)中的重要組成部分之一，是實(shí)現(xiàn)車牌識(shí)別(LPR)系統(tǒng)的關(guān)鍵。針對(duì)不同背景和

40、光照條件下的車輛圖像，提出了一種基于灰度圖像灰度變化特征進(jìn)行車牌定位的方法。依據(jù)車牌中字符的灰度變化以峰、谷規(guī)律分布確定車牌上下邊界，對(duì)掃描行采用灰度跳變法確定車牌左右邊界。</p><p>　　數(shù)字化處理的第一步包含了一系列不同的操作并被稱之為圖像處理。如果傳感器具有非線性特性，就必須予以校正，同樣，圖像的亮度和對(duì)比度也需要改善。通常，還需要進(jìn)行坐標(biāo)變換以消除在成像時(shí)產(chǎn)生的幾何畸變。輻射度校正和幾何校正是最基本

41、的像素處理操作。</p><p>　　在圖像中，對(duì)已知的干擾進(jìn)行校正也是不可少的，比如由于光學(xué)聚焦不準(zhǔn)，運(yùn)動(dòng)模糊，傳感器誤差以及圖像信號(hào)傳輸誤差所引起的干擾。在此還要涉及圖像重構(gòu)技術(shù)，它需要許多間接的成像技術(shù)，比如不直接提供圖像的X射線斷層技術(shù)等。</p><p>　　一套完整的處理步驟對(duì)于物體的分析和識(shí)別是必不可少的。首先，應(yīng)該采用適當(dāng)?shù)倪^(guò)濾技術(shù)以便從其他物體和背景中將所感興趣的物體區(qū)分

42、出來(lái)。實(shí)質(zhì)上就是從一幅圖像（或者數(shù)幅圖像）中抽取出一幅或幾幅特征圖像。要完成這個(gè)任務(wù)最基本的工具就是圖像處理中所使用的求均值和邊緣檢測(cè)、簡(jiǎn)單的相鄰像素分析，以及復(fù)雜的被稱為材質(zhì)描述的模式分析。物體的一個(gè)重要特性就是它的運(yùn)動(dòng)性。檢測(cè)和確定物體運(yùn)動(dòng)性的技術(shù)是必不可少的。隨后，該物體必須從背景中分離出來(lái)，這就意味著具有同樣特性和不同特性的區(qū)域必須被識(shí)別出來(lái)。這個(gè)過(guò)程產(chǎn)生出標(biāo)志圖像。既然已經(jīng)知道了物體精確的幾何形狀，就可以抽取諸如平均灰度值、區(qū)

43、域、邊界以及形成物體的其他參數(shù)等更多的信息。這些參數(shù)可用來(lái)對(duì)物體進(jìn)行分類，這是許多圖像處理應(yīng)用中至關(guān)重要的一步，比如下面一些應(yīng)用：在一個(gè)顯示農(nóng)業(yè)地區(qū)的衛(wèi)星圖像中，想要區(qū)別出不同的果樹，并獲取參數(shù)以估算出成熟情況并監(jiān)測(cè)害蟲情況；</p><p>　　在許多的醫(yī)學(xué)應(yīng)用中，最基本的問(wèn)題是檢查病理變化，最典型的應(yīng)用就是染色體畸變分析；印刷體和手寫體識(shí)別是另一個(gè)例子，圖像處理一出現(xiàn)，人們就開始對(duì)它進(jìn)行著研究，現(xiàn)在依然困難重

44、重。</p><p>　　人們希望能了解得更多一些，也就是試圖理解所讀到的內(nèi)容。這也是圖像處理的最后一個(gè)步驟，即理解所觀察到的景象。當(dāng)我們使用視覺(jué)系統(tǒng)時(shí)，實(shí)際上已或多或少無(wú)意識(shí)地在執(zhí)行這個(gè)任務(wù)。我們能識(shí)別不同的人，可以很輕易地區(qū)分出實(shí)驗(yàn)室和起居室，可以觀察車流以便安全地穿行馬路。我們完成這樣的任務(wù)而并不了解視覺(jué)系統(tǒng)工作的奧秘。</p><p>　　長(zhǎng)久以來(lái)，圖像處理和計(jì)算機(jī)圖形學(xué)被看做兩個(gè)

45、不同的領(lǐng)域。現(xiàn)在，人們?cè)谶@兩個(gè)領(lǐng)域中的知識(shí)都有了極大的提高，并可以解決許多復(fù)雜的問(wèn)題。計(jì)算機(jī)圖形學(xué)正在努力使三維景物的計(jì)算機(jī)圖像達(dá)到照片級(jí)效果。而圖像處理則試圖對(duì)用照相機(jī)實(shí)際拍攝的圖像進(jìn)行重構(gòu)。從這個(gè)意義上講，圖像處理完成的是與計(jì)算機(jī)圖形技術(shù)相反的過(guò)程。但從有關(guān)物體的形狀和特性知識(shí)開始（如圖12-1的底部所示），向上直到獲得一個(gè)二維圖像要運(yùn)用圖像處理和計(jì)算機(jī)圖形技術(shù)，所用到的基本知識(shí)都是一樣的。我們需要了解物體和照明之間的相互關(guān)系，三維

46、景物是如何投影到圖像平面上的等有關(guān)知識(shí)。</p><p>　　圖像處理和計(jì)算機(jī)圖形工作站之間仍然有一些不同之處。但我們應(yīng)該看到，一旦較好地理解了計(jì)算機(jī)圖形技術(shù)和圖像處理之間的相似性和相互關(guān)系，并開發(fā)出了適當(dāng)?shù)挠布到y(tǒng)，一些既可處理計(jì)算機(jī)圖形，又可完成圖像處理任務(wù)的通用工作站就會(huì)出現(xiàn)。多媒體的出現(xiàn)，即文字、圖像、聲音和電影的綜合，將進(jìn)一步加速計(jì)算機(jī)圖形學(xué)和圖像處理的統(tǒng)一。</p><p>　

47、　1980年元月《科學(xué)美國(guó)人》發(fā)表了一幅被稱之為“Plume 2”的著名圖像，它是1979年3月5日通過(guò)宇宙飛船旅行者1號(hào)在木星的衛(wèi)星上探測(cè)到的8次火山爆發(fā)中的第二次。這幅圖像在星際探險(xiǎn)圖像中是一個(gè)里程碑，人們第一次在宇宙中看到了正在爆發(fā)的火山。它也是圖像處理領(lǐng)域的一次偉大勝利。</p><p>　　衛(wèi)星圖像以及宇宙探測(cè)器所獲取的圖像直到近年來(lái)才大量應(yīng)用圖像處理技術(shù)。在這些技術(shù)中，對(duì)計(jì)算機(jī)圖像進(jìn)行數(shù)字化處理以得到

48、想要獲得的效果，比如使圖像的某一部分或某一特性更加明顯。</p><p>　　圖像處理源自于二戰(zhàn)中的攝影偵察。當(dāng)時(shí)，處理操作是通過(guò)光學(xué)方法來(lái)完成的，判讀工作則是由專門精于此道并能確定炸彈襲擊結(jié)果的人員來(lái)做。隨著20世紀(jì)60年代后期衛(wèi)星圖像的出現(xiàn)，更多基于計(jì)算機(jī)的工作便開展起來(lái)彩色合成的衛(wèi)星圖像，有時(shí)的確漂亮得讓人吃驚，它們已經(jīng)成為人類視覺(jué)文化和對(duì)我們這個(gè)行星進(jìn)行認(rèn)知的一個(gè)組成部分。</p><

49、p>　　正如計(jì)算機(jī)圖形學(xué)一樣，直到近幾年，圖像處理仍局限在一些實(shí)驗(yàn)室里使用，只有這些地方才能提供昂貴的圖像處理計(jì)算機(jī)來(lái)滿足處理大量高分辨率圖像的需要。隨著價(jià)格低廉的高性能計(jì)算機(jī)和諸如數(shù)碼相機(jī)及掃描儀這樣的圖像采集設(shè)備的出現(xiàn)，我們已經(jīng)看到圖像處理技術(shù)在向公眾領(lǐng)域轉(zhuǎn)移。經(jīng)典的圖像處理技術(shù)很平常地被圖像設(shè)計(jì)人員用來(lái)處理圖片和生成圖像，比如修復(fù)缺陷，改變色彩等或者通過(guò)圖像邊緣增強(qiáng)這樣的處理來(lái)改變整個(gè)圖片外觀。</p><

50、;p>　　目前圖像處理的主流應(yīng)用是圖像的壓縮，即通過(guò)互聯(lián)網(wǎng)進(jìn)行傳遞或在可視電話和視頻會(huì)議中進(jìn)行移動(dòng)視頻圖像的壓縮?？梢曤娫捠钱?dāng)今結(jié)合計(jì)算機(jī)圖像和傳統(tǒng)圖像處理技術(shù)，以期產(chǎn)生很高壓縮比的交叉領(lǐng)域之一。所有這一切都是圖像的數(shù)字表達(dá)這一不可抗拒的發(fā)展趨勢(shì)的組成部分。事實(shí)上，20世紀(jì)最強(qiáng)大的圖像形式——電視圖像，也將不可避免地融入數(shù)字領(lǐng)域。</p><p>　　圖像處理的特點(diǎn)是針對(duì)不同問(wèn)題有大量不同的算法。有一些是應(yīng)

51、用于每一個(gè)像素的、數(shù)學(xué)的或不依賴上下文的運(yùn)算，比如，可以使用傅里葉變換來(lái)完成圖像濾波操作；還有一些則是算法上的一一可以在圖像中使用復(fù)雜的遞歸策略找出構(gòu)成邊緣的那些像素。</p><p>　　圖像處理操作通常形成計(jì)算機(jī)視覺(jué)系統(tǒng)的一部分。比如，在形狀檢測(cè)操作中輸入圖像可過(guò)濾成高光或顯示圖像邊緣。在計(jì)算機(jī)視覺(jué)系統(tǒng)中．這些處理通常認(rèn)為是低級(jí)操作在計(jì)算機(jī)圖形技術(shù)中，過(guò)濾操作廣泛地用于防止圖像毛邊或采樣失真。</p&g