Title :
Off-line handwritten word recognition (HWR) using a single contextual hidden Markov model
Author :
Chen, Mou-Yon ; Kundu, Amlan ; Zhou, Jian
Author_Institution :
Center of Excellence for Document Anal. & Recognition, State Univ. of New York, Buffalo, NY, USA
Abstract :
A complete scheme for totally unconstrained handwritten word recognition based on a single contextual hidden Markov model (HMM) is proposed. The scheme includes a morphology- and heuristics-based segmentation algorithm and a modified Viterbi algorithm that searches the (l+1)st globally best path based on the previous l best paths. The results of detailed experiments for which the overall recognition rate is up to 89.4% are reported
Keywords :
Markov processes; character recognition; image recognition; image segmentation; Viterbi algorithm; globally best path; heuristics-based segmentation algorithm; morphology-based segmentation algorithm; offline handwritten word recognition; single contextual hidden Markov model; unconstrained handwritten word recognition; Handwriting recognition; Hidden Markov models; Image recognition; Image segmentation; Postal services; Speech processing; Speech recognition; Text analysis;
Conference_Titel :
Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
Conference_Location :
Champaign, IL
Print_ISBN :
0-8186-2855-3
DOI :
10.1109/CVPR.1992.223205
