Character recognition by geometrical moments on structural decompositions
Pasquale Foggia, Carlo Sansone, Francesco Tortorella, Mario Vento · 2002
A novel description method is presented. It is based on the combination of structural and statistical approaches, and is applied to the problem of unconstrained isolated handwritten character recognition. Characters are preliminarily decomposed in terms of structural primitives (circular arcs) and successively described in terms of statistical features (geometrical moments suitably normalized). A multilayer perceptron is adopted in the classification stage. Results of the method on the digits of the ETL Database are reported.