Title :
Recovering writing traces in off-line handwriting recognition: using a global optimization technique
Author_Institution :
Daimler-Benz AG, Ulm, Germany
Abstract :
Off-line handwriting recognition is constrained by the lack of time information. This paper describes an approach to derive sequence information from a written word. The underlying representation of the word used is a graph with nodes and edges resulting from a skeletonization process. The writing path is reconstructed by assuming that the writer has used a path with least curvature, i.e. reconstruction is realized as a global optimization process, which consists of solving a travelling salesman problem
Keywords :
character recognition; graph theory; image reconstruction; image representation; optimisation; travelling salesman problems; character recognition; global optimization; graph representation; image reconstruction; off-line handwriting recognition; skeletonization; travelling salesman problem; writing path; writing trace recovering; Automation; Handwriting recognition; Hardware; Hidden Markov models; Image recognition; Image reconstruction; Personal digital assistants; Skeleton; Traveling salesman problems; Writing;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.546812