外文翻译---图像的边缘检测

1、附：英文资料翻译 图像的边缘检测To image edge examination algorithm research academic reportAbstractDigital 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 charact

2、eristic, 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

3、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

4、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 go

5、od and bad points. 对图像边缘检测算法的研究学术报告摘 要数字图像处理作为一门相对比较年轻的学科, 伴随着计算机技术的飞速发展, 日益得到广泛的 应用 . 边缘作为图像的一种基本特征, 在图像识别,图像分割,图像增强以及图像压缩等的领域中有较为广泛的应用.图像边缘提取的手段多种多样,其中基于亮度的算法,是研究时间最久,理论发展最成熟的方法, 它主要是通过一些差分算子, 由图像的亮度计算其梯度的变化 , 从而检测出边缘, 主要有 Robert, Laplacian, Sobel, Canny, LOG 等算子 . 首先从总体上介绍了数字图像处理及边缘提取的概况, 列举了几种目前

6、常用的边缘提取技术和算法 ,并选取其中两种使用Visual C+ 语言编程实现,通过对两种算法所提取图像结果的比较,研究探讨它们的优缺点.First chapter introduction 1.1 image edge examination introductionThe image edge is one of image most basic characteristics, often is carryingimage majority of informations.But the edge exists in the image irregular structure and i

7、n 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 wit

8、hdraw 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 i

9、nfluence; Also because the edge examination all has in many aspects the extremely important use value, therefore how the people are devoting continuously instudy and solve the structure toleave have the good nature and the good effect edge examination operator question.Inthe usual situation, we may

10、the signal in singular point and the point of discontinuity thought is in the image peripheral point, its nearby gradation change situation may reflectfrom its neighboring picture element gradation distribution gradient. According to this characteristic, we proposed many kinds of edge examination op

11、erator: 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 ef

12、fect 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 correspondingcan bring the flaw which the edge fuzzy

13、 and so on overcomes withdifficulty.Alongwith the wavelet analysis appearance, its good time frequency partialcharacteristic by the widespread application in the imagery processing and in the pattern recognition domain, becomes in the signal processing the commonly used method andthe powerful tool.T

14、hrough 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 e

15、xpresses the image the edge characteristic.When the wavelet transformation criterion reduces, is more sensitive to theimage 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 p

16、attern 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 w

17、ork 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

18、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 t

19、opic. 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 char

20、acteristic 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 supposi

21、tion to the image characteristic type, therefore it has the very strong versatility. 第一章 绪论 1.1 图像边缘检测概论 图像边缘是图像最基本的特征之一, 往往携带着一幅图像的大部分信息. 而边缘存在于图像的 不规则结构和不平稳现象中,也即存在于信号的突变点处,这些点给出了图像轮廓的位置,这些轮 廓常常是我们在图像处理时所需要的非常重要的一些特征条件, 这就需要我们对一幅图像检测并提取出它的边缘. 而边缘检测算法则是图像处理问题中经典技术难题之一,它的解决对于我们进行高层次的特征描述, 识别和理解等有着重大

22、的影响; 又由于边缘检测在许多方面都有着非常重要的使用价值 , 所以人们一直在致力于研究和解决如何构造出具有良好性质及好的效果的边缘检测算子的问题.在通常情况下,我们可以将信号中的奇异点和突变点认为是图像中的边缘点,其附近灰度的变化情况可从它相邻像素灰度分布的梯度来反映.根据这一特点,我们提出了多种边缘检测算子:如 Robert 算子 ,Sobel 算子 ,Prewitt 算子 ,Laplace 算子等 .这些方法多是以待处理像素为中心的邻域作为进行灰度分析的基础,实现对图像 边缘的提取并已经取得了较好的处理效果. 但这类方法同时也存在有边缘像素宽, 噪声干扰较严重等缺点 , 即使采用一些辅助

23、的方法加以去噪,也相应的会带来边缘模糊等难以克服的缺陷.随着小波分析的出现, 其良好的时频局部特性被广泛的应用在图像处理和模式识别领域中, 成为信号处理中常用的手段和有力的工具. 通过小波分析, 可以将交织在一起的各种混合信号分解成不同频率的块信号,而通过小波变换进行边缘检测,可以充分利用其多尺度和多分辨率的性质,真实有效的表达图像的边缘特征.当小波变换的尺度减小时,对图像的细节更加敏感;而当尺度增大时,图像的细节将被滤掉,检测的边缘只是粗轮廓.该特性在模式识别中非常有用,我们可以将此粗轮廓称为图像的主要边缘.如果能将一个图像的主要边缘清晰完整的提取出来,这将对目标分割,识别等后续处理带来极大

24、的便利.总的说来,以上方法都是基于图像的亮度信息来作的工作. 在众多科研工作者的努力下,取得了很好的效果 . 但是,由于图像边缘受到光照等物理条件的影响比较大, 往往使得以上诸多基于亮度的边缘提取方法有着一个共同的缺点, 那就是边缘不连续, 不封闭 . 考虑到相位信息在图像中的重要性以及其稳定的特点, 使得利用相位信息进行图像处理成为新的研究课题. 在本文中即将介绍一种基于相位的图像特征检测方法相位一致性方法 . 它并不是利用图像的亮度信息,而是其相位特点,即假设图像的傅立叶分量相位最一致的点作为特征点.它不但能检 测到阶跃特征, 线特征等亮度特征, 而且能够检测到由于人类视觉感知特性而产生的

25、的马赫带现象. 由于相位一致性不需要对图像的特征类型进行任何假设,所以它具有很强的通用性 . 1.2 image edge definitionThe 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 usua

26、lly 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 t

27、he roof 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 possibili

28、ty 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 qu

29、ite 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 i

30、n 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 intens

31、ity. 1.3 paper selected topic theory significanceThe 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 di

32、scipline 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 u

33、nderstanding.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 di

34、visionhas 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 cont