The design and analysis of spatial data structures
The design and analysis of spatial data structures
ERNEST: A Semantic Network System for Pattern Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maris: map recognition input system
Pattern Recognition
Automatic Learning and Recognition of Graphical Symbols in Engineering Drawings
Selected Papers from the First International Workshop on Graphics Recognition, Methods and Applications
Knowledge-Based Segmentation for Automatic Map Interpretation
Selected Papers from the First International Workshop on Graphics Recognition, Methods and Applications
A String Based Method to Recognize Symbols and Structural Textures in Architectural Plans
GREC '97 Selected Papers from the Second International Workshop on Graphics Recognition, Algorithms and Systems
Information Fusion for Conflict Resolution in Map Interpretation
GREC '97 Selected Papers from the Second International Workshop on Graphics Recognition, Algorithms and Systems
An Interpretation System for Cadastral Maps
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Image interpretation of topographic maps on a medium scale via frame-based modelling
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
An Interpretation System for Cadastral Maps
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Graph based shapes representation and recognition
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Graphical knowledge management in graphics recognition systems
GbRPR'05 Proceedings of the 5th IAPR international conference on Graph-Based Representations in Pattern Recognition
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A universal data model, named DG, is introduced to handle vectorized data uniformly during the whole recognition process. The model supports low level graph algorithms as well as higher level processing. To improve algorithmic efficiency, spatial indexing can be applied. Implementation aspects are discussed as well. An earlier version of the DG model has been applied for interpretation of Hungarian cadastral maps. Although this paper gives examples of map interpretation, our concept can be extended to other fields of graphics recognition.