Title :
A Pattern Deformational Model and Bayes Error-Correcting Recognition System
Author :
Tsai, Wen-Hsiang ; Fu, King-Sun
Abstract :
A pattern deformational model is proposed in this paper. Pattern deformations are categorized into two types: local deformation and structural deformation. A structure-preserving local deformation can be decomposed into a syntactic deformation followed by a semantic deformation, the former being induced on primitive structures and the latter on primitive properties. Bayes error-correcting parsing algorithms are proposed accordingly which not only can perform normal syntax analysis but also can make statistical decisions. An optimum Bayes error-correcting recognition system is then formulated for pattern classification. The system can be considered as a hybrid pattern classifier which uses both syntactic and statistical pattern recognition techniques.
Keywords :
Algorithm design and analysis; Deformable models; Noise shaping; Pattern classification; Pattern recognition; Performance analysis; Shape; Smoothing methods;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMC.1979.4310126