Intelligent vision systems for industry:
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Deutsch |
| Veröffentlicht: |
London [u.a.]
Springer
1997
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007479854&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XXI, 457 S. |
| ISBN: | 3540199691 |
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| 245 | 1 | 0 | |a Intelligent vision systems for industry |c Bruce G. Batchelor and Paul F. Whelan |
| 264 | 1 | |a London [u.a.] |b Springer |c 1997 | |
| 300 | |a XXI, 457 S. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
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| 650 | 7 | |a Vision par ordinateur |2 ram | |
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Datensatz im Suchindex
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|---|---|
| DE-BY-TUM_katkey | 883786 |
| DE-BY-TUM_location | 00 |
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| adam_text | Table of Contents
1 Basic Concepts 1
1.1 Industrial Vision Systems 1
1.1.1 Justification 3
1.1.2 Limitations of Present Systems 4
1.1.3 Flexible Manufacturing Systems 6
1.1.4 Process Control 7
1.2 Systems Engineering 9
1.2.1 Importance of Context 9
1.2.2 Industrial Examples 10
1.3 Intelligent Vision 13
1.3.1 Heuristics and Algorithms 15
1.3.2 Artificial Intelligence (AI) Languages 17
1.4 Book Outline 17
2 Basic Machine Vision Techniques 19
2.1 Representations of Images 19
2.2 Elementary Image Processing Functions 21
2.2.1 Monadic, Point by point Operators 22
2.2.2 Dyadic, Point by point Operators 24
2.2.3 Local Operators 25
2.2.4 Linear Local Operators 25
2.2.5 Non linear Local Operators 28
2.2.6 N tuple Operators 32
2.2.7 Edge Effects 32
2.2.8 Intensity Histogram 33
2.3 Binary Images 35
2.3.1 Measurements on Binary Images 41
2.3.2 Shape Descriptors 43
2.4 Binary Mathematical Morphology 43
2.4.1 Opening and Closing Operations 46
2.4.2 Structuring Element Decomposition 47
2.5 Grey Scale Morphology 49
2.6 Global Image Transforms 51
2.6.1 Hough Transform 51
2.6.2 Two dimensional Discrete Fourier Transform 53
2.7 Texture Analysis 56
2.7.1 Statistical Approaches 56
2.7.2 Co occurrence Matrix Approach 57
2.7.3 Structural Approaches 59
2.7.4 Morphological Texture Analysis 60
XVI
2.8 Implementation Considerations 60
2.8.1 Morphological System Implementation 61
2.9 Commercial Devices 61
2.9.1 Plug in Boards: Frame stores 62
2.9.2 Plug in Boards: Dedicated Function 63
2.9.3 Self contained Systems 63
2.9.4 Turn key Systems 64
2.9.5 Software 64
2.10 Further Remarks 64
3 Intelligent Image Processing 66
3.1 Interactive Image Processing 66
3.1.1 Modus Operandi 67
3.1.2 Prototyping Inspection Systems 67
3.1.3 Building Simple Programs 69
3.1.4 Interaction and Prolog 70
3.2 Introducing Prolog+ 71
3.3 Review of Prolog 73
3.3.1 Sample Program 76
3.3.2 Sample Queries 78
3.4 The Nature of Prolog+ 79
3.5 Prolog+ Programs 81
3.5.1 Recognising Bakewell Tarts 81
3.5.2 Recognising Printed Letters 83
3.5.3 Identifying Table Cutlery 84
3.5.4 Analysing all Visible Objects 87
3.5.5 Recognising a Table Place Setting 87
3.6 Abstract Concepts in Prolog+ 90
3.6.1 Describing a Simple Package 90
3.6.2 Abstract Spatial Relationships 91
3.6.3 Geometric Figures 93
3.7 Implementation of Prolog+ 96
3.7.1 The # Operator 96
3.8 Comments 99
4 Enhanced Intelligent Systems 101
4.1 Prolog+ Environment: A Tool box for Machine Vision 102
4.1.1 Defining New Predicate Names 102
4.1.2 Default Values for Arguments 103
4.1.3 Useful Operators 103
4.1.4 Program Library 106
4.1.5 Auto start 106
4.1.6 Interactive Mode 108
4.1.7 User Extendible Pull down Menus 108
Mechanism for Extending Menus 109
XVII
4.1.8 Command Keys 113
4.1.9 Graphical Display of a Robot Work Cell 115
4.1.10 Speech Synthesis and Recorded Speech 116
4.1.11 On line HELP 117
4.1.12 Cursor 118
4.1.13 Automatic Script Generation and Optimisation 120
4.1.14 Linking to Other Programs 120
HyperCard Controller for a Flexible Inspection Cell 122
4.2 Understanding Simple Spoken Instructions 124
4.2.1 Speech Recognition 124
4.2.2 Natural Language Understanding 127
4.2.3 Automatically Building a Pull down Menu 127
4.2.4 Understanding NL Commands for an (X,Y,0) table 129
4.2.5 Sample Sentences 132
4.2.6 Interpreting the Parser Output 132
4.2.7 Review 133
4.3 Aids for Designing Vision Systems 134
4.3.1 Lighting Advisor 135
Stack Structure 136
Search Mechanisms 136
Remarks About the Lighting Advisor 141
4.3.2 Other Design Aids for Machine Vision 143
4.4 Multi camera Systems 144
4.4.1 Multiplexed video Systems 144
4.4.2 Networked Vision Systems 147
4.4.3 Master Slave System Organisation 150
4.4.4 Remote Queries 152
Interactive Operation of the Remote Process 153
4.4.5 Blackboard 154
Master and Slave Program Elements 155
4.4.6 Controlling the Master Slave System 155
Starting the System 156
Stopping a Slave 156
Passing a Message to the Slave 156
Receiving Data from a Slave 157
Slave Program 157
Blackboard (Snapshot of Database. Changing Constantly) 157
4.4.7 Crash Recovery 158
Programming the Slave from the Master 158
4.5 Comments 158
5 Controlling External Devices 160
5.1 Devices and Signals 160
5.2 Protocols and Signals 161
5.2.1 Interfacing to Commercial Systems 162
XVIII
5.3 Programmable Logic Controller 166
5.4 General Purpose Interface Unit 169
5.4.1 Motivation for the Design 171
5.4.2 Hardware Organisation 172
5.4.3 Programs 173
5.4.4 Digression on Lighting 173
5.4.5 Languages for Robotics 176
5.5 Flexible Inspection Cell, Design Issues 177
5.5.1 Lighting Arrangement 177
5.5.2 Mechanical Handling 178
5.5.3 Cameras and Lenses 179
5.5.4 MMB Host Interface Protocol 180
5.5.5 Additional Remarks 181
5.5.6 HyperCard Control Software for the FIC 183
5.6 Prolog+ Predicates for Device Control 183
5.7 System Calibration 185
5.7.1 FIC Calibration Procedure (Overhead Camera) 186
5.7.2 Calibration, SCARA and Gantry Robots (Overhead Camera) 190
5.7.3 Calibration Procedure (Overhead Narrow view Camera) 191
5.7.4 Calibration Procedure (Side Camera) 193
5.8 Picking up a Randomly Placed Object (Overhead Camera) 194
5.8.1 Program 197
5.9 Grippers 198
5.9.1 Suction Gripper 198
5.9.2 Magnetic Gripper 198
5.9.3 Multi Finger Gripper 199
5.9.4 Further Remarks 200
5.10 Summary 201
6 Colour Image Recognition 206
6.1 Introduction 206
6.2 Applications of Coarse Colour Discrimination 207
6.3 Why is a Banana Yellow? 209
6.4 Machines for Colour Discrimination 213
6.4.1 Optical Filters 213
6.4.2 Colour Cameras 215
6.4.3 Light Sources for Colour Vision 216
6.4.4 Colour Standards 218
6.5 Ways of Thinking about Colour 219
6.5.1 Opponent Process Representation of Colour 220
6.5.2 YIQ Colour Representation 220
6.5.3 HSI, Hue Saturation and Intensity 221
6.5.4 RGB Colour Space: Colour Triangle 221
6.5.5 1 Dimensional Histograms of RGB Colour Separations 224
6.5.6 2 Dimensional Scattergrams 224
XIX
6.5.7 Colour Scattergrams 226
6.6 Programmable Colour Filter (PCF) 227
6.6.1 Implementation of the PCF 228
6.6.2 Programming the PCF 229
6.6.3 Recognising a Single Colour 235
6.6.4 Noise Effects 235
6.6.5 Recognising Multiple Colours 236
6.6.6 Pseudo Colour Display for the PCF 237
6.6.7 Recent Teaching of the PCF Dominates 238
6.6.8 Prolog+ Software for Operating the PCF 239
Plot Colour Scattergram 241
Draw Colour Triangle Outline 242
Clear LUT 242
Store Current LUT 242
Reload Stored PCF 242
Reverting to Monochrome Operation 242
6.6.9 Programming the PCF using the Colour Scattergram 242
6.6.10 Programming the PCF by Image Processing 243
6.6.11 Hue PCF 244
6.6.12 Analysing Output of the Hue PCF 246
6.6.13 Segmented PCF 248
6.6.14 Measuring Colour Similarity and Saturation 248
6.6.15 Detecting Local Colour Changes 249
6.6.16 Colour Generalisation 250
6.7 Colour Recognition in Prolog+ Programs 252
6.7.1 Counting Coloured Objects 252
6.7.2 Recognising a Polychromatic Logo, Program 1 254
6.7.3 Recognising a Polychromatic Logo, Program 2 256
6.7.4 Recognising a Polychromatic Logo, Program 3 257
6.7.5 Multiple Exemplar Approach to Recognition 258
6.7.6 Learning Proportions of Colours in a Scene 260
6.7.7 Superior Program for Learning Colour Proportions 262
6.7.8 Teaching the PCF by Showing 263
6.7.9 Template Matching of Colour Images 266
6.7.10 Using Colour for Object Orientation 269
6.7.11 Approximating an Image by a Set of Overlapping Discs 271
6.7.12 Interpreting Resistor and Capacitor Colour Codes 273
6.8 Discussion and Conclusions 275
7 Applications of Intelligent Vision 295
7.1 Recognition of Printed Patterns 295
7.1.1 Non picture Playing Cards 295
7.1.2 Stars 296
7.1.3 Smiley Faces 297
7.1.4 Alphanumeric Characters 298
XX
Program 299
Comments 301
Logical and Analogue Shape Measurements 302
7.2 Manipulation of Planar Objects 303
7.2.1 Assumptions 303
7.2.2 Significance 304
7.2.3 Simple Shape Measurements 304
7.2.4 Learning and Recognition 306
7.2.5 Program Listing 308
7.2.6 Sample Output of Recognition Phase 310
7.3 Packing and Depletion 311
7.3.1 Geometric Packer Implementation 312
7.3.2 Heuristic Packing Techniques 313
Blob Packing 314
Polygon Packing 316
7.3.3 Performance Measures 319
Predicates 319
7.3.4 Robot Gripper Considerations 321
7.3.5 Packing Scenes with Defective Regions 322
7.3.6 Discussion 323
7.4 Handedness of Mirror Image Components 323
7.4.1 Handedness and Chirality 323
Relating Chirality and Handedness 324
7.4.2 Concavity Trees 326
Formal Definition 328
Generating Concavity Trees 329
Sample Concavity Trees 331
Canonical Form of Concavity Trees 334
Program to find Chirality 336
7.4.3 Properties of Concavity Trees 336
Instability 338
7.4.4 Simpler Tests for Chirality 339
Second Program 340
Third Program 341
Fourth Program 341
Fifth Program 342
7.5 Telling the Time 343
7.5.1 Significance 343
7.5.2 Simplifying Assumptions 344
7.5.3 Lighting 344
7.5.4 First Program 345
7(.5.5 Other Methods 347
T.5.6 Concluding Remarks 348
7.6 Food and Agricultural Products 349
7.6.1 Objective 349
XXI
7.6.2 Industrial Relevance 349
7.6.3 Product Shape, Two dimensions 351
Image Acquisition 352
Rectangular and Circular Biscuits 352
Slices of Bread 355
Locating the Base and Determining Orientation 356
Locating Straight Sides 357
Measuring Overspill 358
Radius of Curvature of Top Edge 358
7.6.4 Analysing the 3D Structure of an Uncut Loaf 360
8 Concluding Remarks 380
References 383
A Proverbs, Opinions and Folklore 390
B Factors to be Considered when Designing a Vision System 401
C General Reference Material 404
D PIP Software Implementation of Prolog+ 414
E Prolog+ and PIP Commands 425
Glossary of Terms 434
Index of Predicates, Operators and Grammar Rules 447
Index 451
|
| any_adam_object | 1 |
| author | Batchelor, Bruce G. 1943- Whelan, Paul F. |
| author_GND | (DE-588)122561279 |
| author_facet | Batchelor, Bruce G. 1943- Whelan, Paul F. |
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| bvnumber | BV011157008 |
| callnumber-first | T - Technology |
| callnumber-label | TA1634 |
| callnumber-raw | TA1634.B37 1997 |
| callnumber-search | TA1634.B37 1997 |
| callnumber-sort | TA 41634 B37 41997 |
| callnumber-subject | TA - General and Civil Engineering |
| classification_rvk | ST 330 |
| classification_tum | DAT 760f |
| ctrlnum | (OCoLC)36083525 (DE-599)BVBBV011157008 |
| dewey-full | 670.42/721 670.42/7 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 670 - Manufacturing |
| dewey-raw | 670.42/7 21 670.42/7 |
| dewey-search | 670.42/7 21 670.42/7 |
| dewey-sort | 3670.42 17 221 |
| dewey-tens | 670 - Manufacturing |
| discipline | Informatik Werkstoffwissenschaften / Fertigungstechnik |
| format | Book |
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| id | DE-604.BV011157008 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T10:07:18Z |
| institution | BVB |
| isbn | 3540199691 |
| language | German |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007479854 |
| oclc_num | 36083525 |
| open_access_boolean | |
| owner | DE-29T DE-91 DE-BY-TUM DE-521 DE-634 |
| owner_facet | DE-29T DE-91 DE-BY-TUM DE-521 DE-634 |
| physical | XXI, 457 S. |
| publishDate | 1997 |
| publishDateSearch | 1997 |
| publishDateSort | 1997 |
| publisher | Springer |
| record_format | marc |
| spellingShingle | Batchelor, Bruce G. 1943- Whelan, Paul F. Intelligent vision systems for industry Vision par ordinateur ram Computer vision Image processing Maschinelles Sehen (DE-588)4129594-8 gnd |
| subject_GND | (DE-588)4129594-8 |
| title | Intelligent vision systems for industry |
| title_auth | Intelligent vision systems for industry |
| title_exact_search | Intelligent vision systems for industry |
| title_full | Intelligent vision systems for industry Bruce G. Batchelor and Paul F. Whelan |
| title_fullStr | Intelligent vision systems for industry Bruce G. Batchelor and Paul F. Whelan |
| title_full_unstemmed | Intelligent vision systems for industry Bruce G. Batchelor and Paul F. Whelan |
| title_short | Intelligent vision systems for industry |
| title_sort | intelligent vision systems for industry |
| topic | Vision par ordinateur ram Computer vision Image processing Maschinelles Sehen (DE-588)4129594-8 gnd |
| topic_facet | Vision par ordinateur Computer vision Image processing Maschinelles Sehen |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007479854&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT batchelorbruceg intelligentvisionsystemsforindustry AT whelanpaulf intelligentvisionsystemsforindustry |
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Teilbibliothek Stammgelände
| Signatur: |
0002 DAT 760f 98 A 77 Lageplan |
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| Exemplar 1 | Ausleihbar Am Standort |