An Experimental Comparison of Range Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Database for Handwritten Text Recognition Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Full English Sentence Database for Off-Line Handwriting Recognition
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Decision trees for filtering large databases of graphs
International Journal of Intelligent Systems Technologies and Applications
Recognition of sequences of graphical patterns
ANNPR'10 Proceedings of the 4th IAPR TC3 conference on Artificial Neural Networks in Pattern Recognition
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In this paper, a methodology for the generation of benchmarks in pattern recognition is described. The patterns are represented by means of an attributed plex language, which are based on plex grammars augmented by attributes. It is shown that the generated patterns are particularly suitable for the extraction of graph-based representations. As a result, databases of artificial pictures and correspondent graphs can be generated. These collections of graphs are very appropriate for benchmarks in the area of structural pattern recognition, since they are originated from a grammar and not from random distributions. The tools for creating the databases are public domain and have been already used for benchmarking artificial neural networks operating on structured domains.