HDevelop User's Manual

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106 CHAPTER 5. PROGRAM EXAMPLES Figure 5.12: Board with electonic devices (left) and the corresponding color value image in the HSV space (right). ÖÑ ´Á×¸ ³³µ ÓÑÔÓ×¿ ´Á×¸ Ê¸ ÖÒ¸ ÐÙµ ØÖÒ×ÖÓÑÖ ´Ê¸ ÖÒ¸ ÐÙ¸ ÀÙ¸ ËØÙÖØÓÒ¸ ÁÒØÒ×ØÝµ ØÖ×ÓÐ ´ËØÙÖØÓÒ¸ ÓÐÓÖ¸ ½¼¼¸ ¾µ ÖÙÓÑÒ ´ÀÙ¸ ÓÐÓÖ¸ ÀÙÓÐÓÖµ ØÖ×ÓÐ ´ÀÙÓÐÓÖ¸ ÐÙ¸ ½½¸ ½¿µ ÓÒÒØÓÒ ´ÐÙ¸ ÐÙÓÒÒØµ ×ÐØ×Ô ´ÐÙÓÒÒØ¸ ÐÙÄÖ¸ ³Ö³¸ ³Ò³¸ ½¼¸ ½¼¼¼¼¼µ ×ÔØÖÒ× ´ÐÙÄÖ¸ ÓÒÒ×ØÓÖ×¸ ³ÖØÒÐ¾³µ ØÖ×ÓÐ ´ÀÙÓÐÓÖ¸ Ê¸ ½¼¸ ½µ ÓÒÒØÓÒ ´Ê¸ ÊÓÒÒØµ ×ÐØ×Ô ´ÊÓÒÒØ¸ ÊÄÖ¸ ³Ö³¸ ³Ò³¸ ½¼¸ ½¼¼¼¼¼µ ×ÔØÖÒ× ´ÊÄÖ¸ Ê××ØÓÖ×¸ ³ÖØÒÐ¾³µ If you look closer at this program segment you will notice some obvious enhancements that can be made. One is necessary due to the color model: The thresholding of the color image chooses all pixels with a certain color. This selection is independent of the color saturation. Thus it might happen that very bright pixels (nearly white pixels) or very dark pixels (nearly black pixels) have the same color value as the components. But you are only looking for stronger colors. For this you select all pixels first whose color is strong, i.e., all pixels with a high saturation. The second enhancement concerns the objects’ shape. As the devices are rectangular you can specify the smallest enclosing rectangle of all connected components to enhance the segments.On the left side of figure 5.13 the resulting components are marked. In a second step, we will search for all ICs. This seems to be easy, as they are rather large and dark. However, some problems emerge due to the bright labels that are printed across some ICs. Thus a simple thresholding alone is not sufficient. In addition you have to combine the segments belonging to one IC. This is done by examining the spatial adjacencies of the segments. A dilation is used to enlarge the regions until they overlap each other. This dilation must not be so large that different ICs are merged. Thus gaps caused by labels have to be smaller than gaps between ICs. Now you can separate the enlarged ICs in their connected <strong>HDevelop</strong> / 2000-11-16
5.7. DEVICES 107 Figure 5.13: Resistors and capacitors (left) and ICs (right). components. Unfortunately, they have become too large by the dilation. Another thresholding for each connected component will detect the dark pixels of each IC. Finally, you can specify the enclosing rectangles analogously to the resistors and the capacitors (see above). ØÖ×ÓÐ ´ÁÒØÒ×ØÝ¸ Ö¸ ¼¸ ¼µ ÐØÓÒÖØÒÐ½ ´Ö¸ ÖÐØ¸ ½¸ ½µ ÓÒÒØÓÒ ´ÖÐØ¸ ÁÄÖµ ÒÒÐ× ´ÁÄÖ¸ ÁÒØÒ×ØÝ¸ ÁÄÖÖÝµ ØÖ×ÓÐ ´ÁÄÖÖÝ¸ Á×Ö¸ ¼¸ ¼µ ×ÔØÖÒ× ´Á×Ö¸ Á¸ ³ÖØÒÐ¾³µ The right side of figure 5.13 shows the resulting ICs. We have to mention two aspects about the program segment above. Here the operator ÒÒÐ× has been used instead of ÖÙ ÓÑÒ. This is necessary as several regions have to be “supplied” with gray values. The situation of previous programs was quite different: there the number of valid pixels of one image has been restricted. From this follows the second point: here the operator ØÖ×ÓÐ gets several images as input. 2 The thresholding is performed in every image. Thus you receive as many regions as input images. Finally, the segmentation of IC contacts has to be done. They are bright and small. Thus it is easy to extract them using a dynamic thresholding (compare chapter 5.3). However, several other tin elements on the board remain a problem, because they have to be distinguished from the IC contacts. This can be done by restricting the search on a region of interest. IC contacts may only appear either on the right or the left side of IC’s. The coarse region of interest is defined by enlarging the IC regions with a following set subtraction. Then the result is resized appropriately by using another dilation. Figure 5.14 shows the operator result on the left side. Now you only have to intersect the result of the thresholding with the region of interest. 2 One matrix is shared by several iconic objects to reduce costs of memory and computation time. HALCON 6.0
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HALCON Version 6.0 MVTec Software G
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About This Manual This manual is a
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Contents 1 Introducing HDevelop 1 1
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Contents iii comment . . . . . . .
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Chapter 1 Introducing HDevelop In f
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1.2. EXAMPLE SESSION 3 Figure 1.1:
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1.2. EXAMPLE SESSION 5 Figure 1.2:
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1.3. ADDITIONAL SOURCES OF INFORMAT
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Chapter 2 Graphical User Interface
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2.3. MAIN WINDOW 11 Figure 2.1: The
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2.3. MAIN WINDOW 13 A security chec
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2.3. MAIN WINDOW 15 a directory whe
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2.3. MAIN WINDOW 17 Figure 2.7: The
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2.3. MAIN WINDOW 19 and not HDevelo
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2.3. MAIN WINDOW 21 Figure 2.10: Ma
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2.3. MAIN WINDOW 23 2.3.2.4 The Men
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2.3. MAIN WINDOW 25 Figure 2.13: On
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2.3. MAIN WINDOW 27 in a graphics w
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2.3. MAIN WINDOW 29 Figure 2.16: On
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2.3. MAIN WINDOW 31 Figure 2.17: Co
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2.3. MAIN WINDOW 33 Figure 2.18: Se
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2.3. MAIN WINDOW 35 Figure 2.20: Se
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2.3. MAIN WINDOW 37 Figure 2.23: Ex
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2.3. MAIN WINDOW 39 output paramete
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2.3. MAIN WINDOW 41 is registered i
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2.3. MAIN WINDOW 43 ËÙ×ØÓÒ×
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2.3. MAIN WINDOW 45 ÏÒÓÛ º ×
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2.3. MAIN WINDOW 47 Figure 2.31: Th
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2.5. OPERATOR WINDOW 49 The program
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2.5. OPERATOR WINDOW 51 Please refe
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2.6. VARIABLE WINDOW 53 operator ha
Page 63 and 64: 2.6. VARIABLE WINDOW 55 aspect rati
Page 65 and 66: 2.7. GRAPHICS WINDOW 57 Figure 2.38
Page 67 and 68: Chapter 3 Language The following ch
Page 69 and 70: 3.2. CONTROL TYPES AND CONSTANTS 61
Page 71 and 72: 3.4. OPERATIONS ON ICONIC OBJECTS 6
Page 73 and 74: 3.5. EXPRESSIONS FOR INPUT CONTROL
Page 85 and 86: 3.6. RESERVED WORDS 77 ÓÖ, ÜÓÖ
Page 87 and 88: 3.8. LIMITATIONS 79 In the followin
Page 89 and 90: Chapter 4 Code Generation The idea
Page 91 and 92: 4.1. CODE GENERATION FOR C++ 83 Ì
Page 93 and 94: 4.1. CODE GENERATION FOR C++ 85 tha
Page 95 and 96: 4.2. CODE GENERATION FOR VISUAL BAS
Page 97 and 98: 4.3. CODE GENERATION FOR C 89 4.3 C
Page 99 and 100: 4.4. GENERAL ASPECTS OF CODE GENERA
Page 101 and 102: Chapter 5 Program Examples This cha
Page 103 and 104: 5.2. CAPILLARY VESSEL 95 ÚÐÓ×Û
Page 105 and 106: 5.2. CAPILLARY VESSEL 97 Figure 5.3
Page 107 and 108: 5.3. PARTICLES 99 each. Now it is e
Page 109 and 110: 5.4. ANNUAL RINGS 101 ÚÐÖÛÒÓ
Page 111 and 112: 5.5. BONDING 103 Figure 5.9: Exampl
Page 113: 5.7. DEVICES 105 Figure 5.11: Calib
Page 117 and 118: 5.8. CELL WALLS 109 Figure 5.15: Mi
Page 119 and 120: 5.10. EXCEPTION HANDLING 111 Figure
Page 121 and 122: 5.11. ROAD SCENE 113 any case. All
Page 123 and 124: 5.11. ROAD SCENE 115 tures. Hence a
Page 125 and 126: Chapter 6 Miscellaneous This chapte
Page 127 and 128: 6.5. RESTRICTIONS 119 Figure 6.1: E
Page 129 and 130: 2 APPENDIX A. CONTROL ÌÙÔÐ½
Page 131 and 132: 4 APPENDIX A. CONTROL Attention For
Page 133 and 134: 6 APPENDIX A. CONTROL Result retur
Page 135 and 136: 8 APPENDIX A. CONTROL ÚÙÔØÛÒ
Page 137 and 138: 10 APPENDIX A. CONTROL HDevelop / 2
Page 139 and 140: 12 APPENDIX B. DEVELOP Attention If
Page 141 and 142: 14 APPENDIX B. DEVELOP Ú ÓÔÒ Û
Page 143 and 144: 16 APPENDIX B. DEVELOP Ú Ò×ÔØ
Page 145 and 146: 18 APPENDIX B. DEVELOP Parallelizat
Page 147 and 148: 20 APPENDIX B. DEVELOP º ÀØ (inp
Page 149 and 150: 22 APPENDIX B. DEVELOP ’black’
Page 151 and 152: 24 APPENDIX B. DEVELOP Parameter º
Page 153 and 154: 26 APPENDIX B. DEVELOP Parameter º
Page 155 and 156: 28 APPENDIX B. DEVELOP If ÊÓÛ½
Page 157 and 158: 30 APPENDIX B. DEVELOP Ú ×Ø ÛÒ
Page 159 and 160: 32 APPENDIX B. DEVELOP Possible Suc
Page 161 and 162: 34 APPENDIX B. DEVELOP See Also Ú
Page 163 and 164: 36 APPENDIX B. DEVELOP HDevelop / 2
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38 APPENDIX C. GLOSSARY Operator wi
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40 Index Ú ×Ø ÔÖØ, 27, 39 Ú
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42 Index Operator Data base, 37 Nam
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44 Index HDevelop / 2000-11-16
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