Master Thesis - Fachbereich Informatik

More documents

Recommendations

Info

3.2. CAMERA SETUP 33 3.2. Camera setup Machine vision applications have high demands on the imaging system, especially if high accuracy and precision is required. The camera and optical system, i.e. the lens, have to be selected with respect to the particular inspection task. This section gives an overview on the imaging system used in this application and how it was selected. 3.2.1. Camera Selection The main criteria for camera selection with respect to the application in this thesis are: Image quality Speed Resolution The image quality is essential to allow for precise measurements. This includes a low signal-to-noise ratio, no or only a little cross-talking between neighboring pixels, and square pixel elements. As introduced in Section 1.3 the system is intended to work in continuous mode. Therefore, the speed, i.e. the possible frame rate, of the camera determines how many images of a tube can be captured within a given time period. Of course, this number is also depending on the velocity of the conveyor. Especially at higher velocities, a fast camera is important, since the idea of multi-image measurements fails if the camera is not able to capture more than one image of each tube that is possible to evaluate. The final frame rate should depend purely on the per frame processing time. This means, the camera must be able to capture at least as many frames as can be processed. Otherwise the camera would be a bottleneck. The frame rate of a camera is closely related to the image resolution. Higher resolutions mean a larger amount of data to be transferred and processed. Thus, there is a tradeoff between resolution and speed. A higher resolution means smaller elements on the CDD sensor array, hence, an object can be imaged more detailed. With respect to length measurements the effective pixel size decreases at a higher resolution, and a pixel represents a smaller unit in the real world. Three cameras have been tested and compared: Sony DFW VL-500 AVT Marlin F-033C AVT Marlin F-046B These cameras are all IEEE 1394 (Firewire) progressive scan CCD cameras. The Sony camera has a 1/3” image device (Sony Wfine CCD) and provides VGA (640× 480) resolution color images at a frame rate of 30 frames per second (fps). It is equipped with an integrated 12× zoom lens which can be adjusted over a motor. The Marlin F-033C is a color camera with a maximum resolution of 656 × 492 pixel in raw mode, while the F-046B is a gray scale camera with a resolution of 780 × 582 pixel in raw mode. Both cameras have a 1/2” image device (SONY IT CCD). The Marlin cameras reach much higher frame rates compared to the Sony. At full resolution, the F-033C
34 CHAPTER 3. HARDWARE CONFIGURATION R1 G1 R2 G2 G3 B1 G4 B2 P1 P2 P3 Figure 3.2: The sensor elements of single chip color cameras like the Marlin F-033C are provided with color filters, so that each sensor element gathers light of a certain range of wavelengths only, corresponding to red, green, and blue respectively. The arrangement of the filters is denoted as BAYER mosaic. Interpolation is needed to compute the missing two channels at each pixel. Image taken from [3]. features 74fps and the F-046B 53fps respectively. Since these cameras do not come with an integrated optical system, a particular lens (C-Mount) must be provided additionally. AmoredetailedspecificationoftheMarlincamerascanbefoundinAppendixB.1. It turned out that the Sony camera is not suited for this particular application. The main reason is the limited frame rate of 30fps, thus, a new image is captured approximately every 30ms. As mentioned before, the camera speed should not be the bottleneck of the application. However, as will be shown in Section 5.3.8, the processing time of one image is significantly less than 30ms, which excludes the Sony camera in this particular application. The Marlin cameras reach much higher frame rates and come with another advantage. Since the tube orientation can be considered as horizontal due to the guide bars as introduced in the previous section, one does not need the whole image height that a camera can provide. It is possible to reduce the image size to user-defined proportions also denoted as area of interest (AOI). This function is used to decrease the number of image rows to be transferred over the firewire connection, but keeping the full resolution in horizontal direction. For example, in a typical setup an image height of 160 pixels is large enough to include the whole region between the guide bars. The reduced image size is about 1/3 of the original size. Combined with a short shutter time, the reduced number of image rows increases the effective frame rate significantly, so it is possible to reach frame rates of > 100fps. The decision whether to use the Marlin F-033C or the F-046B depends mainly on the question if color is a useful feature in this particular application. In general, single chip color cameras like the F-033C map a scene less accurate compared to gray scale cameras if image brightness is considered. This is due to how these cameras are designed. Each sensor cell of a single chip color camera is provided with a color filter for either red (R), green (G), or blue (B) respectively. Without these filters the sensor cells are equal to those in gray scale cameras. Usually, the filters are arranged in a pattern denoted as BAYER mosaic (see Figure 3.2). Within each 2×2 region there are two green, one red, and one blue filter. This distribution is originated in human vision and leads to more natural looking images, since the human optical system is most sensitive to green light. The drawback of this approach is that the resolution of
Page 1 and 2: Fachbereich Informatik Department o
Page 4: Acknowledgments First of all, I wou
Page 8 and 9: Contents Acknowledgments iii Abstra
Page 10 and 11: Contents ix 5.3.7. TubeLength .....
Page 12 and 13: List of Tables 1.1. Rangeoftubetype
Page 14 and 15: 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 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
Page 90 and 91: 4.5. MEASURING POINT DETECTION 75 f
Page 92 and 93: 4.5. MEASURING POINT DETECTION 77 T
Page 94 and 95: 4.5. MEASURING POINT DETECTION 79 -
Page 96 and 97: 4.5. MEASURING POINT DETECTION 81 0
Page 98 and 99:
4.5. MEASURING POINT DETECTION 83 o
Page 100 and 101:
4.5. MEASURING POINT DETECTION 85 (
Page 102 and 103:
4.5. MEASURING POINT DETECTION 87 w
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
Page 128 and 129:
5.3. EXPERIMENTAL RESULTS 113 GTD [
Page 130 and 131:
5.3. EXPERIMENTAL RESULTS 115 gray
Page 132 and 133:
Page 134 and 135:
5.3. EXPERIMENTAL RESULTS 119 (a) (
Page 136 and 137:
5.3. EXPERIMENTAL RESULTS 121 (a) (
Page 138 and 139:
Page 140 and 141:
5.3. EXPERIMENTAL RESULTS 125 Total
Page 142 and 143:
5.3. EXPERIMENTAL RESULTS 127 Color
Page 144 and 145:
5.3. EXPERIMENTAL RESULTS 129 Task
Page 146 and 147:
5.4. DISCUSSION AND FUTURE WORK 131
Page 148 and 149:
6. Conclusion In this thesis a func
Page 150:
Appendix 135
Page 153 and 154:
138 APPENDIX A. PROFILE ANALYSIS IM
Page 155 and 156:
140 APPENDIX A. PROFILE ANALYSIS IM
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.
show all

Master Thesis - Fachbereich Informatik

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?