Master Thesis - Fachbereich Informatik

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4. Length Measurement Approach While the previous chapter focused on the hardware setup, this chapter will present the methodical part of the system. After a brief overview, the different steps including the camera calibration and teach-in step as well as the tube localization, measuring point detection, tube tracking and the good/bad classification are introduced. All assumptions and the model knowledge used throughout these steps are presented before. 4.1. System Overview The fundamental concept of the developed system is a so called multi-image measuring strategy. This means, the goal is to measure each tube not only once, but in as many images as possible while it is in the visual field of the camera. The advantage of this approach is that the decision whether a particular tube meets the length tolerances can be made based on a set of measurements. The total length is computed by averaging over these single measurements leading to more robust results. Furthermore, the system is less sensitive to detection errors. Depending on the conveyor velocity and the tube length one can reach between 2 and 10 measurements per tube. The system is designed to work without any external trigger that provokes the camera to grab a frame depending on a certain event, e.g. a tube passing a light barrier. Instead, the camera is operated in continuous mode, i.e. images are captured at a constant frame rate using an internal trigger. The absence of an external trigger, however, requires fast algorithms to evaluate whether a frame is useful, i.e. whether a measurement is possible. In addition, the system must be able to track a tube while it is in the visual field of the camera to assign measurements to this particular tube. Accurate length measurements of tubes require the very accurate detection of the tube edges. A template based tube edge localization method has been developed allowing for reliable, subpixel accurate detection resultsevenunderthepresenceoftubeedgelikebackgroundclutter. Oncethereisevidence that a tube has left the visual field of the camera, all corresponding measurements have to be evaluated with respect to the given target length and tolerances. The resulting good/bad decision must be delegated to the external controller handling the air pressure based blow out mechanism. Model knowledge regarding the inspected tubes under the constrained conditions is exploited if possible to optimize the processing. Before any measurements can be performed, the system has to be calibrated and trained to the particular target length. This includes camera positioning, radial distortion compensation and an online teach-in step. Figure 4.1 gives an overview on the different stages of the system. It can also be seen as outline of this section. The underlying methods and concepts will be introduced in the following in more detail. Throughout this chapter all parameters will be handled abstract. Corresponding value assignments used in the experiments are given in Section 5.1.1. 51
52 CHAPTER 4. LENGTH MEASUREMENT APPROACH No No Camera calibration Teach-In Next image Tube localization Measurement possible? Yes Measuring point detection Length measuring Tube passed? Yes Total length computation Good/bad classification Blow out control Figure 4.1: System overview. After camera calibration and a teach-in step the system evaluates the acquired images continuously. If a tube is located and assigned as measurable, the exact measuring points on the tube edges are detected and the tube length is calculated. Once a tube has passed the visual field of the camera, the computed total length is compared to the allowed tolerances for a good/bad classification. Finally, the blow out controller is notified whether the current tube is allowed to pass.
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Fachbereich Informatik Department o
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Acknowledgments First of all, I wou
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Contents Acknowledgments iii Abstra
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Contents ix 5.3.7. TubeLength .....
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List of Tables 1.1. Rangeoftubetype
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List of Figures 2.1. AccuracyandPre
Page 16 and 17: 1. Introduction Heat shrinkable tub
Page 18 and 19: 1.2. PROBLEM STATEMENT 3 hazards, r
Page 20 and 21: 1.4. RELATED WORK 5 Length [mm] Tol
Page 22 and 23: 1.5. THESIS OUTLINE 7 The vision pa
Page 24 and 25: 2. Technical Background 2.1. Visual
Page 26 and 27: 2.1. VISUAL MEASUREMENTS 11 (a) Fig
Page 28 and 29: 2.1. VISUAL MEASUREMENTS 13 Figure
Page 30 and 31: 2.1. VISUAL MEASUREMENTS 15 � xd
Page 32 and 33: 2.2. ILLUMINATION 17 tubes alternat
Page 34 and 35: 2.2. ILLUMINATION 19 effect of comp
Page 36 and 37: 2.3. EDGE DETECTION 21 i 2 i 1 0 (a
Page 38 and 39: 2.3. EDGE DETECTION 23 N × 1 kerne
Page 40 and 41: 2.3. EDGE DETECTION 25 These operat
Page 42 and 43: 2.3. EDGE DETECTION 27 (a) 0 ◦ (b
Page 44 and 45: 2.4. TEMPLATE MATCHING 29 accuracy
Page 46 and 47: 3. Hardware Configuration This chap
Page 48 and 49: 3.2. CAMERA SETUP 33 3.2. Camera se
Page 50 and 51: 3.2. CAMERA SETUP 35 eachcolorchann
Page 52 and 53: 3.2. CAMERA SETUP 37 Figure 3.4: Co
Page 54 and 55: 3.2. CAMERA SETUP 39 adjusting scre
Page 56 and 57: 3.2. CAMERA SETUP 41 further distan
Page 58 and 59: 3.3. ILLUMINATION 43 f V 12mm 129mm
Page 60 and 61: 3.3. ILLUMINATION 45 (a) (b) (c) Fi
Page 62 and 63: 3.3. ILLUMINATION 47 (a) (b) Figure
Page 64 and 65: 3.4. BLOW OUT MECHANISM 49 A light
Page 68 and 69: 4.2. MODEL KNOWLEDGE AND ASSUMPTION
Page 74 and 75: 4.3. CAMERA CALIBRATION 59 4.2.7. B
Page 76 and 77: 4.3. CAMERA CALIBRATION 61 Figure 4
Page 78 and 79: 4.3. CAMERA CALIBRATION 63 is compu
Page 80 and 81: 4.4. TUBE LOCALIZATION 65 (a) (b) F
Page 82 and 83: 4.4. TUBE LOCALIZATION 67 � 1 Psm
Page 84 and 85: 4.4. TUBE LOCALIZATION 69 Global Th
Page 86 and 87: 4.4. TUBE LOCALIZATION 71 but also
Page 88 and 89: 4.4. TUBE LOCALIZATION 73 Global Re
Page 90 and 91: 4.5. MEASURING POINT DETECTION 75 f
Page 92 and 93: 4.5. MEASURING POINT DETECTION 77 T
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Page 104 and 105: 4.6. MEASURING 89 side of the tube,
Page 106 and 107: 4.6. MEASURING 91 fcor(x) =−(c1x
Page 108 and 109: 4.7. TEACH-IN 93 inthemeasuringplan
Page 110 and 111: 4.7. TEACH-IN 95 The pair of a pixe
Page 112 and 113: 5. Results and Evaluation 5.1. Expe
Page 114 and 115: 5.1. EXPERIMENTAL DESIGN 99 between
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5.1. EXPERIMENTAL DESIGN 101 where
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5.1. EXPERIMENTAL DESIGN 103 Ground
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5.2. TEST SCENARIOS 105 enough, the
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5.3. EXPERIMENTAL RESULTS 107 The t
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5.3. EXPERIMENTAL RESULTS 109 Detec
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5.3. EXPERIMENTAL RESULTS 111 Lengt
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5.3. EXPERIMENTAL RESULTS 113 GTD [
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5.3. EXPERIMENTAL RESULTS 115 gray
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5.3. EXPERIMENTAL RESULTS 119 (a) (
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5.3. EXPERIMENTAL RESULTS 121 (a) (
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5.3. EXPERIMENTAL RESULTS 125 Total
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5.3. EXPERIMENTAL RESULTS 127 Color
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5.3. EXPERIMENTAL RESULTS 129 Task
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5.4. DISCUSSION AND FUTURE WORK 131
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6. Conclusion In this thesis a func
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Appendix 135
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138 APPENDIX A. PROFILE ANALYSIS IM
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140 APPENDIX A. PROFILE ANALYSIS IM
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142 APPENDIX B. HARDWARE COMPONENTS
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144 APPENDIX B. HARDWARE COMPONENTS
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146 Bibliography [18] C. Demant, B.
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148 Bibliography [51] K.K. Pingle.
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Master Thesis - Fachbereich Informatik

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