Integration of visual inter-word constraints and linguistic knowledge in degraded text recognition

Authors:
Tao Hong
Affiliations:
State University of New York at Buffalo, Buffalo, NY
Venue:
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Year:
1994

Citing 2
Cited 2

Word association norms, mutual information, and lexicography

Computational Linguistics
Degraded text recognition using word collocation and visual inter-word constraints

ANLC '94 Proceedings of the fourth conference on Applied natural language processing

Degraded text recognition using word collocation and visual inter-word constraints

ANLC '94 Proceedings of the fourth conference on Applied natural language processing
Degraded text recognition using word collocation and visual inter-word constraints

ANLC '94 Proceedings of the fourth conference on Applied natural language processing

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Abstract

Degraded text recognition is a difficult task. Given a noisy text image, a word recognizer can be applied to generate several candidates for each word image. High-level knowledge sources can then be used to select a decision from the candidate set for each word image. In this paper, we propose that visual inter-word constraints can be used to facilitate candidate selection. Visual inter-word constraints provide a way to link word images inside the text page, and to interpret them systematically.