An Automatic Circuit Diagram Reader with Loop-Structure-Based Symbol Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special Issue on Industrial Machine Vision and Computer Vision Technology:8MPart
Fuzzy Sets and Systems - Special issue on fuzzy methods for computer vision and pattern recognition
Topological relations in the world of minimum bounding rectangles: a study with R-trees
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
MARCO: MAp Retrieval by COntent
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human-based spatial relationship generalization through neural/fuzzy approaches
Fuzzy Sets and Systems
A New Way to Represent the Relative Position between Areal Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Architectural symbol recognition using a network of constraints
Pattern Recognition Letters
Symbol Recognition by Error-Tolerant Subgraph Matching between Region Adjacency Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Symbol Recognition: Current Advances and Perspectives
GREC '01 Selected Papers from the Fourth International Workshop on Graphics Recognition Algorithms and Applications
Spatial Reasoning with Topological Information
Spatial Cognition, An Interdisciplinary Approach to Representing and Processing Spatial Knowledge
Efficient Attributed Graph Matching and Its Application to Image Analysis
ICIAP '95 Proceedings of the 8th International Conference on Image Analysis and Processing
A model for image generation and symbol recognition through the deformation of lineal shapes
Pattern Recognition Letters
An online composite graphics recognition approach based on matching of spatial relation graphs
International Journal on Document Analysis and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Symbol Recognition with Kernel Density Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning spatial relations in object recognition
Pattern Recognition Letters
Pattern Recognition Methods for Querying and Browsing Technical Documentation
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Inductive Logic Programming for Symbol Recognition
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
A new shape descriptor defined on the Radon transform
Computer Vision and Image Understanding
Learning Context-Sensitive Shape Similarity by Graph Transduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
A dynamic-rule-based framework of engineering drawing recognition and interpretation system
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Robust and precise circular arc detection
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
Unified pairwise spatial relations: an application to graphical symbol retrieval
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
Spatio-structural symbol description with statistical feature add-on
GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges
Spectra of shape contexts: An application to symbol recognition
Pattern Recognition
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In this paper, we present a method for symbol recognition based on the spatio-structural description of a 'vocabulary' of extracted visual elementary parts. It is applied to symbols in electrical wiring diagrams. The method consists of first identifying vocabulary elements into different groups based on their types (e.g., circle, corner). We then compute spatial relations between the possible pairs of labelled vocabulary types which are further used as a basis for building an attributed relational graph that fully describes the symbol. These spatial relations integrate both topology and directional information. The experiments reported in this paper show that this approach, used for recognition, significantly outperforms both structural and signal-based state-of-the-art methods.