Iconic indexing by 2-D strings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of handwritten digits using template and model matching
Pattern Recognition
Knowledge-based interpretation of utility maps
Computer Vision and Image Understanding
A graph-constructive approach to solving systems of geometric constraints
ACM Transactions on Graphics (TOG)
Symbol Recognition by Error-Tolerant Subgraph Matching between Region Adjacency Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
A new type of recurrent neural network for handwritten character recognition
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
Solving Geometric Constraints by a Graph-Constructive Approach
IV '99 Proceedings of the 1999 International Conference on Information Visualisation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generating 3D building models from architectural drawings: a survey
IEEE Computer Graphics and Applications - Special issue title on generating 3D building models a VR playground for teaching math
A 2D geometric constraint solver using a graph reduction method
Advances in Engineering Software
Leveraging cognitive factors in securing WWW with CAPTCHA
WebApps'10 Proceedings of the 2010 USENIX conference on Web application development
From engineering diagrams to engineering models: Visual recognition and applications
Computer-Aided Design
Symbol recognition using bipartite transformation distance and angular distribution alignment
GREC'05 Proceedings of the 6th international conference on Graphics Recognition: ten Years Review and Future Perspectives
A method for symbol spotting in graphical documents
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Automatic analysis and sketch-based retrieval of architectural floor plans
Pattern Recognition Letters
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In this paper, we propose a framework for engineeringdrawings recognition using a case-based approach. Thekey idea of our scheme is that, interactively, the userprovides an example of one type of graphic object in anengineering drawing, then the system learns the graphicalknowledge of this type of graphic object from the exampleand uses this learned knowledge to recognize or searchfor similar graphic objects in engineering drawings. Thescheme emphasizes the following three distinctcharacteristics: automatism, run-time-ness, androbustness. We summarized five types of geometricconstraints to represent the generic graphical knowledge.We also developed two algorithms for case-basedgraphical knowledge acquisition and knowledge-basedgraphics recognition, respectively. Experiments haveshown that our proposed framework is both efficient andeffective for recognizing various types of graphic objectsin engineering drawings.