Fault Tolerant Recognition Method of Handwritten Chinese Characters Based on Double Weights Elliptical Neuron
Applied Biomimetic Pattern Recognition to replace “differentiation” of characteristic sample by machine “cognition”, a novel method of handwritten Chinese characters recognition is presented. A double weights elliptical neuron is used to cover four basic kinds of handwritten Chinese characters stroke segment. The topological property among the stroke segment neurons is analyzed. Nine style of Chinese characters stroke with fault tolerance are combined. Imitated typing methods of human Chinese characters font code, the style and number of stroke neurons which have redundant fault tolerant shapes are counted. A kind of characteristic knowledge data-base table of handwritten Chinese characters and the sample data-base of standard printed Chinese characters and fault tolerant matching rules are built. Simple and more complex handwritten Chinese characters in SCUT-IRAC database are tested. The method is proved to be close to human fault tolerance and veracity.
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