外文翻譯---圖像的邊緣檢測(cè)

精品文檔 1歡迎下載 附 英文資料翻譯附 英文資料翻譯 圖像的邊緣檢測(cè) ToTo imageimage edgeedge examinationexamination algorithmalgorithm researchresearch academicacademic reportreport AbstractAbstract Digital image processing took a relative quite young discipline is following the computer technology rapid development day by day obtains the widespread application The edge took the image one kind of basic characteristic in the pattern recognition the image division the image intensification as well as the image compression and so on in the domain has a more widespread application Image edge detection method many and varied in which based on brightness algorithm is studies the time to be most long the theory develops the maturest method it mainly is through some difference operator calculates its gradient based on image brightness the change thus examines the edge mainly has Robert Laplacian Sobel Canny operators and so on LOG First as a whole introduced digital image processing and the edge detection survey has enumerated several kind of at present commonly used edge detection technology and the algorithm and selects two kinds to use Visual the C language programming realization through withdraws the image result to two algorithms the comparison the research discusses their good and bad points 對(duì)圖像邊緣檢測(cè)算法的研究學(xué)術(shù)報(bào)告 摘 要 數(shù)字圖像處理作為一門相對(duì)比較年輕的學(xué)科 伴隨著計(jì)算機(jī)技術(shù)的飛速發(fā)展 日益得到廣 泛的 應(yīng)用 邊緣作為圖像的一種基本特征 在圖像識(shí)別 圖像分割 圖像增強(qiáng)以及圖像壓縮 等的領(lǐng)域中有 較為廣泛的應(yīng)用 圖像邊緣提取的手段多種多樣 其中基于亮度的算法 是研 究時(shí)間最久 理論發(fā)展最成熟的方法 它主要是通過一些差分算子 由圖像的亮度計(jì)算其梯 度的變化 從而檢測(cè)出邊緣 主要有 Robert Laplacian Sobel Canny LOG 等算子 精品文檔 2歡迎下載 首先從總體上介紹了數(shù)字圖像處理及邊緣提取的概況 列舉了幾種目前常用的邊緣提取技 術(shù)和 算法 并選取其中兩種使用 Visual C 語言編程實(shí)現(xiàn) 通過對(duì)兩種算法所提取圖像結(jié) 果的比較 研 究探討它們的優(yōu)缺點(diǎn) FirstFirst chapterchapter introductionintroduction 1 1 1 1 imageimage edgeedge examinationexamination introductionintroduction The image edge is one of image most basic characteristics often is carrying image majority of informations But the edge exists in the image irregular structure and in not the steady phenomenon also namely exists in the signal point of discontinuity place these spots have given the image outline position these outlines are frequently we when the imagery processing needs the extremely important some representative condition this needs us to examine and to withdraw its edge to an image But the edge examination algorithm is in the imagery processing question one of classical technical difficult problems its solution carries on the high level regarding us the characteristic description the recognition and the understanding and so on has the significant influence Also because the edge examination all has in many aspects the extremely important use value therefore how the people are devoting continuously in study and solve the structure to leave have the good nature and the good effect edge examination operator question In the usual situation we may the signal in singular point and the point of discontinuity thought is in the image peripheral point its nearby gradation change situation may reflect from its neighboring picture element gradation distribution gradient According to this characteristic we proposed many kinds of edge examination operator If Robert operator Sobel operator Prewitt operator Laplace operator and so on These methods many are wait for the processing picture element to carry on the gradation analysis for the central neighborhood achievement the foundation realized and has already obtained the good processing effect to the image edge extraction But this kind of method simultaneously also exists has the edge picture element width the noise jamming is serious and so on the shortcomings even if uses some auxiliary methods to perform the denoising also corresponding can bring the flaw which the edge fuzzy and so on overcomes with difficulty Along with the wavelet analysis appearance its good time frequency partial characteristic by the 精品文檔 3歡迎下載 widespread application in the imagery processing and in the pattern recognition domain becomes in the signal processing the commonly used method and the powerful tool Through the wavelet analysis may interweave decomposes in the same place each kind of composite signal the different frequency the block signal but carries on the edge examination through the wavelet transformation may use its multi criteria and the multi resolution nature fully real effective expresses the image the edge characteristic When the wavelet transformation criterion reduces is more sensitive to the image detail But when the criterion increases the image detail is filtered out the examination edge will be only the thick outline This characteristic is extremely useful in the pattern recognition we may be called this thick outline the image the main edge If will be able an image main edge clear integrity extraction this to the goal division the recognition and so on following processing to bring the enormous convenience Generally speaking the above method all is the work which does based on the image luminance information In the multitudinous scientific research worker under has obtained the very good effect diligently But because the image edge receives physical condition and so on the illumination influences quite to be big above often enables many to have a common shortcoming based on brightness edge detection method that is the edge is not continual does not seal up Considered the phase information in the image importance as well as its stable characteristic causes using the phase information to carry on the imagery processing into new research topic In this paper soon introduces one kind based on the phase image characteristic examination method phase uniform method It is not uses the image the luminance information but is its phase characteristic namely supposition image Fourier component phase most consistent spot achievement characteristic point Not only it can examine brightness characteristics and so on step characteristic line characteristic moreover can examine Mach belt phenomenon which produces as a result of the human vision sensation characteristic Because the phase uniformity does not need to carry on any supposition to the image characteristic type therefore it has the very strong versatility 第一章 緒論 1 1 圖像邊緣檢測(cè)概論 圖像邊緣是圖像最基本的特征之一 往往攜帶著一幅圖像的大部分信息 而邊緣存在于圖 精品文檔 4歡迎下載 像的 不規(guī)則結(jié)構(gòu)和不平穩(wěn)現(xiàn)象中 也即存在于信號(hào)的突變點(diǎn)處 這些點(diǎn)給出了圖像輪廓的位 置 這些輪 廓常常是我們?cè)趫D像處理時(shí)所需要的非常重要的一些特征條件 這就需要我們 對(duì)一幅圖像檢測(cè)并提 取出它的邊緣 而邊緣檢測(cè)算法則是圖像處理問題中經(jīng)典技術(shù)難題之 一 它的解決對(duì)于我們進(jìn)行高 層次的特征描述 識(shí)別和理解等有著重大的影響 又由于邊 緣檢測(cè)在許多方面都有著非常重要的使 用價(jià)值 所以人們一直在致力于研究和解決如何構(gòu) 造出具有良好性質(zhì)及好的效果的邊緣檢測(cè)算子的 問題 在通常情況下 我們可以將信號(hào)中 的奇異點(diǎn)和突變點(diǎn)認(rèn)為是圖像中的邊緣點(diǎn) 其附近灰度的 變化情況可從它相鄰像素灰度分 布的梯度來反映 根據(jù)這一特點(diǎn) 我們提出了多種邊緣檢測(cè)算子 如 Robert 算子 Sobel 算子 Prewitt 算子 Laplace 算子等 這些方法多是以待處理像素為中心的鄰域作為進(jìn)行灰度分析的基礎(chǔ) 實(shí)現(xiàn) 對(duì)圖像 邊緣的提取并已經(jīng)取得了較好的處理效果 但這類方法同時(shí)也存在有邊緣像素寬 噪聲干擾較嚴(yán)重 等缺點(diǎn) 即使采用一些輔助的方法加以去噪 也相應(yīng)的會(huì)帶來邊緣模糊等難 以克服的缺陷 隨著小 波分析的出現(xiàn) 其良好的時(shí)頻局部特性被廣泛的應(yīng)用在圖像處理和 模式識(shí)別領(lǐng)域中 成為信號(hào)處理 中常用的手段和有力的工具 通過小波分析 可以將交織 在一起的各種混合信號(hào)分解成不同頻率的 塊信號(hào) 而通過小波變換進(jìn)行邊緣檢測(cè) 可以充分 利用其多尺度和多分辨率的性質(zhì) 真實(shí)有效的表 達(dá)圖像的邊緣特征 當(dāng)小波變換的尺度減小 時(shí) 對(duì)圖像的細(xì)節(jié)更加敏感 而當(dāng)尺度增大時(shí) 圖像的 細(xì)節(jié)將被濾掉 檢測(cè)的邊緣只是粗輪廓 該 特性在模式識(shí)別中非常有用 我們可以將此粗輪廓稱為 圖像的主要邊緣 如果能將一個(gè)圖像 的主要邊緣清晰完整的提取出來 這將對(duì)目標(biāo)分割 識(shí)別等后 續(xù)處理帶來極大的便利 總的 說來 以上方法都是基于圖像的亮度信息來作的工作 在眾多科研工作者的努力下 取得了 很好的效果 但是 由于圖像邊緣受到光照等物理?xiàng)l件的 影響比較大 往往使得以上諸多基 于亮度的邊緣提取方法有著一個(gè)共同的缺點(diǎn) 那就是邊緣不連續(xù) 不封閉 考慮到相位信 息在圖像中的重要性以及其穩(wěn)定的特點(diǎn) 使得利用相位信息進(jìn)行圖像處理成 為新的研究課 題 在本文中即將介紹一種基于相位的圖像特征檢測(cè)方法 相位一致性方法 它并不是 利用圖像 的亮度信息 而是其相位特點(diǎn) 即假設(shè)圖像的傅立葉分量相位最一致的點(diǎn)作為特征 點(diǎn) 它不但能檢 測(cè)到階躍特征 線特征等亮度特征 而且能夠檢測(cè)到由于人類視覺感知特 性而產(chǎn)生的的馬赫帶現(xiàn)象 由于相位一致性不需要對(duì)圖像的特征類型進(jìn)行任何假設(shè) 所以它 具有很強(qiáng)的通用性 1 2 1 2 imageimage edgeedge definitiondefinition The image majority main information all exists in the image edge the main performance for the image partial characteristic discontinuity is in the image the gradation change quite fierce place also is the signal which we usually said has the strange change place The strange signal the gradation change which moves towards along the edge is fierce usually we divide the edge for the step shape and the roof shape two kind of types as shown in Figure 1 1 In the step edge two side grey levels have the obvious change But the roof 精品文檔 5歡迎下載 shape edge is located the gradation increase and the reduced intersection point May portray the peripheral point in mathematics using the gradation derivative the change to the step edge the roof shape edge asks its step the second time derivative separately To an edge has the possibility simultaneously to have the step and the line edge characteristic For example on a surface changes from a plane to the normal direction different another plane can produce the step edge If this surface has the edges and corners which the regular reflection characteristic also two planes form quite to be smooth then works as when edges and corners smooth surface normal after mirror surface reflection angle as a result of the regular reflection component can produce the bright light strip on the edges and corners smooth surface such edge looked like has likely superimposed a line edge in the step edge Because edge possible and in scene object important characteristic correspondence therefore it is the very important image characteristic For instance an object outline usually produces the step edge because the object image intensity is different with the background image intensity 1 3 1 3 paperpaper selectedselected topictopic theorytheory significancesignificance The paper selected topic originates in holds the important status and the function practical application topic in the image project The so called image project discipline is refers foundation discipline and so on mathematics optics principles the discipline which in the image application unifies which accumulates the technical background develops The image project content is extremely rich and so on divides into three levels differently according to the abstract degree and the research technique Imagery processing image analysis and image understanding As shown in Figure 1 2 in the chart the image division is in between the image analysis and the imagery processing its meaning is the image division is from the imagery processing to the image analysis essential step also is further understands the image the foundation The image division has the important influence to the characteristic The image division and based on the division goal expression the characteristic extraction and the parameter survey and so on transforms the primitive image as a more abstract more compact form causes the high level image analysis and possibly understands into But the edge examination is the image division core content therefore the edge examination holds the important status and the