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ICPR
2002
IEEE

An Iterative Algorithm for Optimal Style Conscious Field Classification

15 years 16 days ago
An Iterative Algorithm for Optimal Style Conscious Field Classification
Modeling consistency of style in isogenous fields of patterns (such as character patterns in a word from the same font or writer) can improve classification accuracy. Since such patterns are interdependent, the Bayes classifier requires maximization of a probability score over all fieldlabels, which are exponentially more numerous with increasing field length. The iterative field classification algorithm prioritizes field-labels, for computation of probability scores, according to an upper bound on the score. Factorizability of the upper bound score allows dynamic prioritization of field-labels. Experiments on classification of numeral field patterns demonstrate computational efficiency of the algorithm.
Prateek Sarkar
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2002
Where ICPR
Authors Prateek Sarkar
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