Abstract
In this paper we analyse theoretical foundations of syntactic pattern recognition and its relationships with mathematical linguistics, structural pattern recognition, and statistical pattern recognition. We point out that all the above mentioned methods are based on two fundamental operations: the combination of parts into wholes and abstraction. We provide examples of those operations in different contexts. Finally, we note that at this level of generalisation, all three main approaches to pattern recognition (structural, statistical and syntactic) can be merged into one powerful method. We outline a system based on these principles and intended to be used for the recognition of unconstrained handwriting.
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Keywords
- Mathematical Linguistics
- Graph Grammar
- Statistical Pattern Recognition
- Syntactical Parser
- Syntactic Pattern Recognition
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
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M. Venguerov, Generalised syntactic pattern recognition and its application to the off-line handwriting analysis, Ph.D. Thesis, Department of Computer Science, Trinity College Dublin, October 1998.
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© 1998 Springer-Verlag Berlin Heidelberg
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Venguerov, M., Cunningham, P. (1998). Generalised syntactic pattern recognition as a unifying approach in image analysis. In: Amin, A., Dori, D., Pudil, P., Freeman, H. (eds) Advances in Pattern Recognition. SSPR /SPR 1998. Lecture Notes in Computer Science, vol 1451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033319
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DOI: https://doi.org/10.1007/BFb0033319
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