图像边缘检测算法-英文文献-翻译-中英文翻译

安徽工业大学毕业设计英文资料翻译image edge examination algorithmAbstract 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.Foreword In image processing, as a basic characteristic, the edge of the image, which is widely used in the recognition, segmentation,intensification and compress of the image, is often applied to high-level domain.There are many kinds of ways to detect the edge. Anyway, there are two main techniques: one is classic method based on the gray grade of every pixel; the other one is based on wavelet and its multi-scale characteristic. The first method, which is got the longest research,get the edge according to the variety of the pixel gray. The main techniques are Robert, Laplace, Sobel, Canny and LOG algorithm. The second method, which is based on wavelet transform, utilizes the Lipschitz exponent characterization of the noise and singular signal and then achieve the goal of removing noise and distilling the real edge lines. In recent years, a new kind of detection method, which based on the phase information of the pixel, is developed. We need hypothesize nothing about images in advance. The edge is easy to find in frequency domain. Its a reliable method. In chapter one, we give an overview of the image edge. And in chapter two, some classic detection algorithms are introduced. The cause of positional error is analyzed, and then discussed a more precision method in edge orientation. In chapter three, wavelet theory is introduced. The detection methods based on sampling wavelet transform, which can extract maim edge of the image effectively, and non-sampling wavelet transform, which can remain the optimum spatial information, are recommended respectively. In the last chapter of this thesis, the algorithm based on phase information is introduced. Using the log Gabor wavelet, two-dimension filter is constructed, many kinds of edges are detected, including Mach Band, which indicates it is a outstanding and bio-simulation method。May all the work in this paper is of some value to research and applications of image edge detection.First chapter introduction 1.1 image edge examination introductionThe 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 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。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 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 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 paper selected topic theory significance 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 function in the image project.Therefore the edge examination research always is in the image engineering research the hot spot and the focal point, moreover the people enhance unceasingly to its attention and the investment。1.4 this article prime tasks 1.4.1 Algorithm contentIntroduced and has analyzed the classics image edge examination algorithm, summarized each algorithm good and bad points, has given the image edge examination result, and emphatically take the LOG algorithm as the example, embarked from the noise and the edge shape viewpoint has analyzed the reason which the edge position error produced; Introduced in one kind of LOG algorithm the quite precise definite edge method。 1.4.2 Wavelet theoryHas studied the wavelet elementary theory, summarized the signal as well as the noise Lip index nature, and in based on in the non-sampling wavelet transformation image characteristic extraction algorithm foundation, unifies the auto-adapted denoising method, has made certain improvement to this method, obtained the quite satisfactory effect, denoising ability had the quite big enhancement; Then introduced one kind based on the sampling wavelet examination image main edge method。 1.4.3 Novel algorithmThe system has studied one kind quite novel based on the phase image characteristic extraction algorithm - - phase uniform algorithm, and has given its simple algorithm.Has given in the unidimensional situation algorithm simulation step, analyzed expanded to the two-dimensional method, and explained by the edge examination result the phase uniform algorithm conformed to the human vision characteristic。1.5 this article content arrangementIn the first chapter, the author has given an outline explanation to the image edge examination, and explained carries on the image edge examination the vital significance.In second chapter, the system introduced the quite classical image edge examination operator and the concrete realization principle, have analyzed each algorithm existence insufficiency by the edge examination result.Finally, from the noise influence and edge shape obtaining, take the LOG algorithm as the example, has analyzed the reason which the false edge as well as edge shifting produces.Finally introduced in one kind of LOG algorithm the quite precise definite edge method.In third chapter, the author system introduced the present quite popular wavelet theory, and introduced emphatically the multi-criterion concept and the signal Lip index, and by the noise and the signal Lip index characteristic, carries on the extraction in the non-sampling wavelet transformation foundation to the image edge.In order to strengthen the edge image anti-chirp ability, but also the algorithm has made certain improvement regarding this, the auto-adapted denoising method will use in the edge detection, has obtained the satisfying effect.Finally also introduces one kind based on the sampling wavelet examination image main edge method.In the this article fourth chapter, introduced one kind quite novel based on the phase image characteristic extraction algorithm - - phase uniform algorithm.From unidimensional algorithm introduction obtaining, has given under the unidimensional signal simulation result, and expands gradually two-dimensionally.Explained through the simulation result this algorithm robustness quite is strong, moreover conforms to humanitys visual system performance.Second chapter classical image edge examination algorithmThis chapter first simply introduced a classics step edge examination essential method in 2.1.Then 2.2 and 2.3 distinctions elaborated specifically the classical derivative operator and the linear filtering operator realization method, and has given each algorithm result comparison in 2.4.In 2.5, compared with the concrete analysis noise and the edge shape the reason which produced to the edge pointing accuracy influence as well as the false edge, and has given in the unidimensional situation simulation result, has drawn the conclusion.In 2.6, the image positive and negative edge which picks out using the LOG algorithm, compared with the precise localization image real edge, the final output was two value single picture element image.2.1 classical edge examination essential methodWe knew that, the edge examination essence is uses some algorithm to withdraw in the image the object and the background junction demarcation line.We define the edge for the image in the gradation occur the rapid change region boundary.The image gradation change situation may use the image gradation distribution the gradient to reflect, therefore we may use the partial image differential technology to obtain the edge examination operator.The edge examination algorithm has the following four steps ( its process as shown in Figure2-1): Filter: The edge examination algorithm mainly is based on an image intensity step and the second time derivative, but the derivative computation is very sensitive to the noise, therefore must use the filter to improve and the noise related edge detector performance.Needs to point out that, the majority filter have also caused the edge intensity loss while noise reduction, therefore, strengthens the edge and between the noise reduction needs compromised.Enhancement: Strengthens the edge the foundation is determines the image each neighborhood intensity the change value.The enhancement algorithm may (or partial) the intensity value has the neighborhood the remarkable change spot to reveal suddenly.The edge strengthens is generally completes through the computation gradient peak-to-peak value.Examination: Has many point gradient peak-to-peak value in the image quite to be big, but these in the specific application domain not all is the edge, therefore should use some method to determine which select is the peripheral points.The simple edge examination criterion is the gradient peak-to-peak value threshold value criterion.Localization: If some application situation request definite edge position, then the edge position may come up the estimate in the sub-picture element resolution, the edge position also may estimate.In the edge examination algorithm, the first three steps use extremely universally.This is because under the majority situations, needs the edge detector to point out merely the edge appears in image some picture element neighbor, but is not unnecessary to point out the edge the exact location or the direction.The edge examines the error usually is refers to the edge to classify the error by mistake, namely distinguished the vacation edge the edge retains, but distinguished the real edge the vacation edge removes.The edge error of estimation is describes the edge position and the lateral error with the probability statistical model.We examine the edge the error and the edge error of estimation differentiate, is because their computational method is completely different, its error model completely is also different.The edge examination is examines