Contextual stochastic model for structural patterns

The theory of contextual stochastic modeling of structurally complex and variant patterns like handwritten Chinese characters is presented. The key lies in capturing the contextual information of the strokes in the character image which is segmented into regions systematically. A model for a character captures the region-region and region-pixel stochastic relationship. An unknown image is recognized by computing the pseudo likelihood of identifying its pixels to regions of each model. Based on this theory, an off-line, large vocabulary, hand-written character recognizer has been constructed.