Knowledge-Directed Interpretation of Mechanical Engineering Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Knowledge-based interpretation of utility maps
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Document zone content classification and its performance evaluation
Pattern Recognition
An interactive example-driven approach to graphics recognition in engineering drawings
International Journal on Document Analysis and Recognition
A general framework for the evaluation of symbol recognition methods
International Journal on Document Analysis and Recognition
A symbol spotting approach in graphical documents by hashing serialized graphs
Pattern Recognition
On the use of geometric matching for both: isolated symbol recognition and symbol spotting
GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges
Bag-of-GraphPaths descriptors for symbol recognition and spotting in line drawings
GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges
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Many methods of graphics recognition have been developed throughout the years for the recognition of pre-segmented graphics symbols but very few techniques achieved the objective of symbol spotting and recognition together in a generic case. To go one step forward through this objective, this paper presents an original solution for symbol spotting using a graph represen-tation of graphical documents. The proposed strategy has two main step. In the first step, a graph based representation of a document image is generated that includes selection of description primitives (nodes of the graph) and organisation of these features (edges). In the second step the graph is used to spot interesting parts of the image that potentially correspond to symbols. The sub-graphs associated to selected zones are then submitted to a graph matching algorithm in order to take the final decision and to recognize the class of the symbol. The experimental results obtained on different types of documents demonstrates that the system can handle different types of images without any modification.