Title :
Contextual stochastic model for structural patterns
Author_Institution :
Dept. of Comput. Sci., Hong Kong Univ., Hong Kong
Abstract :
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
Keywords :
handwritten character recognition; image segmentation; optical character recognition; stochastic processes; character image segmentation; contextual stochastic model; hand-written Chinese characters; handwritten Chinese characters; off-line large-vocabulary hand-written character recognizer; pixel identification; pseudo likelihood; region-pixel stochastic relationship; region-region stochastic relationship; structural patterns; structurally complex patterns; variant patterns; Computer science; Context modeling; Hidden Markov models; Image generation; Image recognition; Image segmentation; Pixel; Production; Stochastic processes; Vocabulary;
Conference_Titel :
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4778-1
DOI :
10.1109/ICSMC.1998.727505