《机器视觉》PPT课件.ppt

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1、nTeacher:Prof.LiuYuncainReferencebooks:1.MachineVision,byRamerhJian,etal(MajorReference)2.ComputerVision,byDamaH.Ballard,etal.3.Vision,ByDavidMarr.4.IntroductoryTechniquesfor3-DComputerVision,byEmanueleTrucco.5.ComputerVisionandImageProcessing,byScattE.Umbaugh.计算机视觉课程计算机视觉课程COMPUTERVISION 6.Algorith

2、mforImageProcessingandComputerVision,byJ.R.Parker.7.机器视觉，贾云得 编著8.计算机视觉的理论和实践，李介谷著9.计算机视觉计算机理论与算法基础，马颂德著 Rule of gradingHomework:10%Examination:60%Project:30%Important Deadlines:Handinprojectproposal:May11,2005Handinprojectreport:July6,2005AllwritteninChinese(中文书写)FinalExamination:July6,2005Course 1I

3、ntroductionn1.What is Computer VisionnComputer vision aims to recover usefulinformationabouta(3D)scenefromits2Dprojections(images).n3Ddepth/3Dstructuren3Dmotionanalysisn3Dsurfacesandorientationnstatusof3Dobjects,soonnmeaningoftheactionsof3DobjectsEvery task is tough since it is to be understood from

4、 flat images!Computer vision is also called as:Machine visionRobot visionImage understandingScene analysis(in early years)课程内容：课程内容：1)绪论(Introduction)2)图象滤波(ImageFiltering)3)二进制图象处理(BinaryImageProcessing)4)区域(Region)5)边缘检测(EdgeDetection)6)立体视觉(Stereo)7)运动的理解与估值(Motion)8)轮廓(Contours)9)纹理(Texture)10)图

5、象光度学(Shading)11)光流场(OpticFlows)12)系统校准(Calibration)13)曲线与曲面(CurvesandSurfaces)14)动态视觉(DynamicVision)15)三维识别(ObjectRecognition)2.Relatedfields image processing computer vision pattern recognition artificial Intelligence neural network psychophysics 3.PerspectiveProjection pin-holecameramodelnprojecti

6、oncenter(i.e.,camera)isattheoriginofscenecoordinatesystemwithopticaxisofcamerapointingtoz-axisdirectionofcoordinatesnoriginofimagecoordinatesystemislocatedat(0,0,f)ofscenecoordinatesystem(fisfocuslengthofthecamera),theX-andY-axesofimagecoordinatesareparallelwithx-andy-axesofscenecoordinates,respecti

7、velyncameradoesnothaveanylensdistortions.xoyoXYP(X,Y)P(x,y,z)LlnP0focuslength=frRz(1)Image point (2)Image Line 3D line l is projected onto image plane through projecting plane to get image line L:Let we use a vector to represent the image line L of l.Since We have,orIt is the equation of projecting

8、plane,the normal is .Thus,we will use the normal of the projecting plane of 3D line to denote image plane by.4.Digital ImagenSampling:digitalize in image plane(directions)say,and so on.nquantization:digitalize in image intensity,say 8 bits(256 levels).for an images having only 2 gray levels,we call it as binary image.OjiOXYImage of 64 gray levelBinary image