Master Thesis - Fachbereich Informatik

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4.5. MEASURING POINT DETECTION 75 for measuring. An overview of the algorithm is shown in Listing 4.1. A size filter operation, which can be parametrized with respect to the given target length, is used to remove too small foreground segments (e.g. caused by dirt on the conveyor belt). The output of the algorithm is either one large background segment (i.e. all foreground segments have been removed if existed since they did not fulfill the criteria) or three segments in the form BG-TUBE-BG. In the later case, the peaks belonging to the left and right boundary of the remaining foreground segment are finally verified with respect to the sign of the derivative. With the derivative operator used, the position of the left boundary must result in a negative first-order derivative value (bright-dark edge) and the right boundary in a positive value (dark-bright edge). If the predicted tube boundaries are consistent with this last criterion, they are used to define two local ROIs of width WROI as starting point for a more precise detection of the measuring points. The local ROI height is defined over the distance between the two guide bars. ThemergingofthesegmentsisalinearoperationinthecomplexityofO(NΩ). Since it is only allowed to reclassify a former foreground segment into background in this procedure and never vice versa, Step2 of the algorithm is repeated only once if at all. Hence, the algorithm terminates for sure. If all segment are classified as TUBE in the first step, an error is returned. This error indicates the presence of state full (See Figure 4.2(i)). The reason can be due to a too small field of view of the camera or to a missing spacing between consecutive tubes. In any case it is not possible to perform a measuring. Since this state is critical compared to other states that can not be used for measuring, it is important to detect this situation. In practice, if this situation occurs an alert must be produced. 4.5. Measuring Point Detection The previous sections described a fast method to distinguish whether a frame is useful or not. If a measuring is possible, two regions around the potential left and right boundary of a tube to be measured are the output of this first step. In the following, the exact tube boundaries have to be detected with subpixel accuracy. 4.5.1. Edge Enhancement As introduced in Section 2.3 there is a large number of approaches for edge detection. Four common methods including the Sobel operator, Laplace operator, Canny edge detector [13] and a steerable filter edge detector based on the derivative of a parametrized Gaussian have been applied to test images. The results can be found in Table 4.2. It includes experiments with two transparent tubes (left boundary) of the same sequence and one black tube boundary. All tubes have a inner diameter of 8mm. The difference in size between the transparent and black tubes is due to a different camera-object distance. As can be seen the edge of the transparent tubes can differ in brightness, contrast and background pattern between frames. The goal was to find an edge detection operation that adequately extracts the tube boundaries under the presence of background structure and noise, and which is computational inexpensive in addition.
76 CHAPTER 4. LENGTH MEASUREMENT APPROACH Input Input SOBELX SOBELY Gaussian 5x5 (a) Gaussian 5x5 (v) Laplace Gaussian 7x7 (a) Canny (50/100) Canny (90/230) Canny (185/210) Gaussian 7x7 (v) Gaussian 11x11 (a) Gaussian 11x11 (v) Table 4.2: Comparison of different edge detectors. The parameters of the Canny edge detector indicate the lower and upper threshold. The Gaussian derivative based edge detection results are all of first-order. An (a) indicates edges of all orientations (in discrete steps of 5 ) are enhanced with a steerable filter approach, while (v) represents only vertical edges.
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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
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1. Introduction Heat shrinkable tub
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1.2. PROBLEM STATEMENT 3 hazards, r
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1.4. RELATED WORK 5 Length [mm] Tol
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1.5. THESIS OUTLINE 7 The vision pa
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2. Technical Background 2.1. Visual
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2.1. VISUAL MEASUREMENTS 11 (a) Fig
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2.1. VISUAL MEASUREMENTS 13 Figure
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2.1. VISUAL MEASUREMENTS 15 � xd
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2.2. ILLUMINATION 17 tubes alternat
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2.2. ILLUMINATION 19 effect of comp
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2.3. EDGE DETECTION 21 i 2 i 1 0 (a
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2.3. EDGE DETECTION 23 N × 1 kerne
Page 40 and 41: 2.3. EDGE DETECTION 25 These operat
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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 66 and 67: 4. Length Measurement Approach Whil
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
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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
Page 116 and 117: 5.1. EXPERIMENTAL DESIGN 101 where
Page 118 and 119: 5.1. EXPERIMENTAL DESIGN 103 Ground
Page 120 and 121: 5.2. TEST SCENARIOS 105 enough, the
Page 122 and 123: 5.3. EXPERIMENTAL RESULTS 107 The t
Page 124 and 125: 5.3. EXPERIMENTAL RESULTS 109 Detec
Page 126 and 127: 5.3. EXPERIMENTAL RESULTS 111 Lengt
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Page 130 and 131: 5.3. EXPERIMENTAL RESULTS 115 gray
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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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