TY - CHAP
T1 - Resolving Ambiguities in Toponym Recognition in Cartographic Maps
AU - Gelbukh, Alexander
AU - Levachkine, Serguei
AU - Han, Sang Yong
PY - 2004
Y1 - 2004
N2 - To date many methods and programs for automatic text recognition exist. However there are no effective text recognition systems for graphic documents. Graphic documents usually contain a great variety of textual information. As a rule the text appears in arbitrary spatial positions, in different fonts, sizes and colors. The text can touch and overlap graphic symbols. The text meaning is semantically much more ambiguous in comparison with standard text. To recognize a text of graphic documents, it is necessary first to separate it from linear objects, solids, and symbols and to define its orientation. Even so, the recognition programs nearly always produce errors. In the context of raster-to-vector conversion of graphic documents, the problem of text recognition is of special interest, because textual information can be used for verifi- . cation of vectorization results (post-processing). In this work, we propose a method that combines OCR-based text recognition in raster-scanned maps with heuristics specially adapted for cartographic data to resolve the recognition ambiguities using, among other information sources, the spatial object relationships. Our goal is to form in the vector thematic layers geographically meaningful words correctly attached to the cartographic objects.
AB - To date many methods and programs for automatic text recognition exist. However there are no effective text recognition systems for graphic documents. Graphic documents usually contain a great variety of textual information. As a rule the text appears in arbitrary spatial positions, in different fonts, sizes and colors. The text can touch and overlap graphic symbols. The text meaning is semantically much more ambiguous in comparison with standard text. To recognize a text of graphic documents, it is necessary first to separate it from linear objects, solids, and symbols and to define its orientation. Even so, the recognition programs nearly always produce errors. In the context of raster-to-vector conversion of graphic documents, the problem of text recognition is of special interest, because textual information can be used for verifi- . cation of vectorization results (post-processing). In this work, we propose a method that combines OCR-based text recognition in raster-scanned maps with heuristics specially adapted for cartographic data to resolve the recognition ambiguities using, among other information sources, the spatial object relationships. Our goal is to form in the vector thematic layers geographically meaningful words correctly attached to the cartographic objects.
UR - http://www.scopus.com/inward/record.url?scp=35048857534&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-25977-0_7
DO - 10.1007/978-3-540-25977-0_7
M3 - Capítulo
AN - SCOPUS:35048857534
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 75
EP - 86
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Llados, Josep
A2 - Kwon, Young-Bin
PB - Springer Verlag
ER -