Character recognition without segmentation
Identifieur interne : 002C16 ( Main/Exploration ); précédent : 002C15; suivant : 002C17Character recognition without segmentation
Auteurs : J. Rocha [Espagne] ; T. PavlidisSource :
- IEEE Transactions on Pattern Analysis and Machine Intelligence [ 0162-8828 ] ; 1995.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Méthode statistique.
English descriptors
- KwdEn :
- Algorithms, Application, Broken character recognition, Character recognition, Character recognition without segmentation, Character segmentation, Database systems, Hidden Markov models, Homeomorphic subgraph matching, Knowledge based systems, Markov processes, Mathematical models, Relative neighborhood graph, Statistical methods, Theory, Touching character recognition.
Abstract
A segmentation-free approach to OCR is presented as part of a knowledge-based word interpretation model. This new method is based on the recognition of subgraphs hemeomorphic to previously defined prototypes of characters. The characters are detected in the order defined by matching quality. Each subgraph that is recognized is introduced as a node in a directed net that compiles different alternative of interpretation of the features in the feature graph. The method allows the recognition of characters that overlap or that are underlined. A final search for the optimal path under certain criteria gives best interpretation of the word features.
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream PascalFrancis, to step Corpus: 000A47
- to stream PascalFrancis, to step Curation: 000952
- to stream PascalFrancis, to step Checkpoint: 000A27
- to stream Main, to step Merge: 002D80
- to stream Main, to step Curation: 002C16
Le document en format XML
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