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Recognition of graphical symbols
Jonk, A.
Publication date
2002
Link to publication
Citation for published version (APA):
Jonk, A. (2002). Recognition of graphical symbols.
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Contents s
11 I n t r o d u c t i o n 1 1.11 Recognizing formal drawings 2
1.22 T h e problem with generic strategies 4
1.2.11 Linking the phases 4 1.2.22 Generic symbol description 6
1.33 Symbols 8 1.3.11 Algorithms for symbol recognition 9
1.44 Defining a detector 10 1.4.11 Demands on detectors 11
1.55 A modular architecture 13
1.66 This thesis 15 1.6.11 C h a p t e r 2: detecting arrows 17
1.6.22 C h a p t e r 3: a passive galley detector 17 1.6.33 Chapter 4: an active1 galley detector 17 1.6.44 C h a p t e r 5: an active dashed line detector 17 1.77 Appendix: Categorization of symbols in utility maps 18
1.7.11 Fixed symbols 18 1.7.22 Regular symbols 19 1.7.31.7.3 Irregular symbols 20 1.7.44 C o m p o u n d symbols 21 22 A c a s e s t u d y in p e r f o r m a n c e a n a l y s i s of r e c o g n i t i o n of g r a p h -icall s i g n s 2 7 2.11 Arrow model 29 2.22 Related work 29 2.33 Arrow Detector 31 2.3.11 Line detection 33 2.3.22 Arrowhead detection 33 2.3.33 Selection and grouping 33
üü C O N T E N T S 2.44 Arrowhead detection 35 2.4.11 Extract image-part 35 2.4.22 Pixelcount 35 2.4.33 Robust line-fitting 36 2.4.44 Hough transform 39 2.4.55 Template matching 41 2.55 Experiments 44 2.5.11 Performance on real images 44
2.5.22 Performance on synthetic images 47 2.5.33 Performance in a map interpretation system 49
2.5.44 Speed 50 2.5.55 Analysis 50 2.GG Conclusions 51
33 A Line Tracker 55
3.11 Line modelling and detection 57 3.1.11 Shape modelling 57 3.1.22 Transsection modelling k detection of line points . . . . 58
3.22 The context of the line tracker 59
3.33 The Line Tracker 00 3.3.11 Finding extension points 01
3.3.22 Evaluating extension points 03 3.3.33 Selecting an extension point 05
3.3.44 Parameter selection 65 3.3.55 Computational complexity 65
3.44 Experiments 66 3.55 Application of the linetracker 71
3.5.11 Experiments 75
3.66 Conclusions 75
44 Grouping Lines by Fitting Splines 81
4.11 Grouping 83 4.22 Grouping applied to curvilinear structures 85
4.2.11 Line model 86 4.2.22 The grouping cue SS 4.2.33 Constructing the grouping hierarchy 93
4.2.44 The appropriate hierarchy level 95
4.33 Results 98 4.3.11 Alternative grouping cues 99
CONTENTSS iü
4.4.11 Initialization stage 101 4.4.22 Iteration stage 101 4.4.33 Average computational complexity 103
4.55 Comparison with other work 104 4.5.11 Comparison on a typical image 107
4.5.22 Robustness, invariance and complexity 107
4.66 Conclusions 109 4.77 Appendix: T h e minimal spline through a set of line segments . I l l
55 G r a m m a t i c a l I n f e r e n c e of D a s h e d L i n e s 119
5.11 T h e definition of a dashed line 121
5.22 Object detection 122 5.33 Matching a g r a m m a r against a string 122
5.3.11 Cyclic graph matching 123 5.3.22 Cyclic group matching applied to dashed line detection 126
5.3.33 Complexity 128 5.44 Finding the optimal cyclic group 129
5.4.11 Heuristics for general solutions 129
5.4.22 Substrings 134 5.4.33 Complexity analysis 135
5.4.44 Imposing a m a x i m u m on the size of the cyclic group . . 138
5.55 Experiments 138 5.66 Conclusions 141 5.77 Appendix: Substring probabilities 142
