Master Thesis - Fachbereich Informatik

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5.4. DISCUSSION AND FUTURE WORK 131 (a) Background only (b) Background + Tubes (c) Masked spectrum (d) Source Image (e) Filtered Image Figure 5.23: Background suppression in the frequency domain. (a) Fourier transform of an image of an empty conveyor. (b) Fourier transform of (d). (c) Certain frequencies have been removed by hand indicated by the black regions. (e) Inverse Fourier transform of the filtered spectrum. The characteristic vertical background pattern could be reduced quite well while thetubeedgesarepreserved. The experiments have shown that tubes of 8mm diameter are most robust against deformations. While thinner tubes of 6mm diameter tend to be bent, tubes of 12mm may be elliptical in the cross-section. In both cases the accuracy and precision decreases. The question is whether such deformations are only caused by the way the tubes have been stored, transported and handled throughout the experiments in the laboratory or if they also occur at production. The later can be assumed, at least in a certain amount. A telecentric lens could overcome the problem of perspective occurring with deformed 12mm tubes. A less cost expensive improvement would be to measure not only the length, but also the height of a tube in the image. A larger height indicates the tube is closer to the camera and vice versa. The calibration factor relating pixels to mm could be defined as a function ofthetubeheight.Obviously,thisrequiresamorecomplexteach-instep. Another potential source of deviations in the measurements is the tube orientation. The guide bars restrict the maximum tube rotation to a minimum. The remaining error has been approximated. Although it is very small, it could be even further reduced by tilting the whole conveyor slightly around its longitudinal axis. The angular orientation guarantees that all tubes will roll to the lower guide bar. If the guide bar is horizontal in the image, so will be the tubes. Accordingly the camera position has to be adapted to reestablish the fronto-orthogonal view. The proposed camera positioning method is independent of the orientation of the conveyor and the camera in 3D space.
132 CHAPTER 5. RESULTS AND EVALUATION The blow out mechanism was tested successfully in the prototype setup. The advantage of this mechanism is that it works almost independent of the conveyor velocity and the position of the light barrier relative to the measuring area. One has to assure only that no tube passes the light barrier before the good/bad decision of the measuring system reaches the blow out controller. One drawback of the current strategy is the sensitivity to ghosts. If the system detects a tube where actually no tube is, the resulting classification of the ghost is send to the controller anyhow and stored in the FIFO memory. Since a ghost is never detected by the light barrier, the good/bad decision of the ghost is still in the memory when the next tube passes the light barrier. Instead of considering the decision belonging to this tube (appended to the FIFO memory) the decision of the ghost is evaluated. This leads to a loss of synchronization, i.e. a tube T is related to the decision of tube T − 1. Over time this effect can increase and the reliability of the system is obviously violated. A potential solution of this problem can be achieved by replacing the FIFO memory by a single register that is able to store only the latest decision. Without loss of generality a0inthisregistermightcorrespondtoblowingoutthenexttubewhilea1indicatesthe next tube can pass. The register is set to 0 by default. Each time the inspection system measures a tube to be within the allowed tolerances a signal is send to the controller that sets the bit in the register to 1. As soon as the tube has passed the light barrier, the register is reset to 0. This has to be done before the next tube is measured. Therefore the light barrier has to be placed quite close to the measuring area. The advantage of this approach is that the memory contains always the current decision belonging to the tube that passes the light barrier next. A timer can be used to reset the register if no tube intersects the light barrier within the expected time. Thus, ghosts become uncritical. Furthermore, since the register is reset each time, this helps also to prevent the problemsofnondetectedtubes,i.e. tubesthathavepassedthevisualfieldofthecamera without being measured. In the outlier experiment (see Section 5.3.6) the false positive rate increased drastically if tubes could not be detected. In this case the system does not send a good/bad decision for the missed tube to the controller. The light barrier, however, detects every tube independent of being measured or not. With the single register strategy these tubes are blown out by default. Thus, only tubes that have been measured by the system and meet the allowed tolerances are able to pass the blow out nozzle. If tubes are not detected at all or measurements do not result in a meaningful length value (e.g. the standard deviation of the single measurements is too large), the corresponding tubes define another group U including all unsure measurements that can not definitely be assigned to G ′ 0 , G′ −,orG ′ +. All tubes of this class should be blown out by default to ensure no outlier can pass the quality control. These tubes do not have to be considered as rejections, but could be measured by hand afterward or recirculated to be inspected again by the vision-based measuring system depending on the frequency of occurrence. The experiments have shown that more than 80% of the total processing time is needed for the template based edge localization. In the current implementation the left and right ROI are processed sequential. One possible optimization could be to parallelize this problem. This means, the computation within the left and right ROI could be performed in separate threads to exploit the power of curret dual core architectures. This is possible, since the processing in the two ROIs is independent of each other.
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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
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2.3. EDGE DETECTION 25 These operat
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2.3. EDGE DETECTION 27 (a) 0 ◦ (b
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2.4. TEMPLATE MATCHING 29 accuracy
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3. Hardware Configuration This chap
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3.2. CAMERA SETUP 33 3.2. Camera se
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3.2. CAMERA SETUP 35 eachcolorchann
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3.2. CAMERA SETUP 37 Figure 3.4: Co
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3.2. CAMERA SETUP 39 adjusting scre
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3.2. CAMERA SETUP 41 further distan
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3.3. ILLUMINATION 43 f V 12mm 129mm
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3.3. ILLUMINATION 45 (a) (b) (c) Fi
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3.3. ILLUMINATION 47 (a) (b) Figure
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3.4. BLOW OUT MECHANISM 49 A light
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4. Length Measurement Approach Whil
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4.2. MODEL KNOWLEDGE AND ASSUMPTION
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4.3. CAMERA CALIBRATION 59 4.2.7. B
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4.3. CAMERA CALIBRATION 61 Figure 4
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4.3. CAMERA CALIBRATION 63 is compu
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4.4. TUBE LOCALIZATION 65 (a) (b) F
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4.4. TUBE LOCALIZATION 67 � 1 Psm
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4.4. TUBE LOCALIZATION 69 Global Th
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4.4. TUBE LOCALIZATION 71 but also
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4.4. TUBE LOCALIZATION 73 Global Re
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4.5. MEASURING POINT DETECTION 75 f
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4.5. MEASURING POINT DETECTION 77 T
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4.5. MEASURING POINT DETECTION 79 -
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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
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Page 130 and 131: 5.3. EXPERIMENTAL RESULTS 115 gray
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Page 153 and 154: 138 APPENDIX A. PROFILE ANALYSIS IM
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Page 157 and 158: 142 APPENDIX B. HARDWARE COMPONENTS
Page 159 and 160: 144 APPENDIX B. HARDWARE COMPONENTS
Page 161 and 162: 146 Bibliography [18] C. Demant, B.
Page 163 and 164: 148 Bibliography [51] K.K. Pingle.
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Master Thesis - Fachbereich Informatik

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