Title :
Character spotting using image-based stochastic models
Author :
Kim, Seon-Kyu ; Sin, Bong-Kee ; Lee, Seong-Whan
Author_Institution :
Pukyong Nat. Univ., South Korea
fDate :
6/23/1905 12:00:00 AM
Abstract :
This paper concerns the modeling of character images by a Markov-like stochastic template that is constructed in the form of the pseudo 2D HMM. Being constructed directly from the image templates, the models can be composed in real time. Preliminary test results in digit recognition and Korean Hangul character spotting show the feasibility of the proposed method, especially in the context of incremental location of keywords
Keywords :
hidden Markov models; optical character recognition; real-time systems; Korean Hangul character spotting; Markov-like stochastic template; character image modeling; digit recognition; hidden Markov model; image templates; image-based stochastic models; incremental keyword location; pseudo 2D HMM; real-time model composition; Character recognition; Hidden Markov models; Image converters; Markov random fields; Optical character recognition software; Pixel; Silicon compounds; Speech recognition; Stochastic processes; Testing;
Conference_Titel :
Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7695-1263-1
DOI :
10.1109/ICDAR.2001.953755
