Proceedings of the International Conference on Document Analysis and Recognition · 2007 · 42 citations · 10 references
ComputingComputer ScienceComputer VisionNatural Language ProcessingText AnalyticsDocument Image AnalysisNamed Entity RecognitionOptical Character RecognitionPattern RecognitionTopographic MappingWord RecognitionFont RecognitionIntelligent Document ProcessingOcr CorrectionText DetectionWord Segmentation
Topographic paper maps are a common support for geographical information. This paper proposes an automatic method to extract and recognize toponyms from such maps. The method uses image segmentation and connected‑component processing, filtering to ensure plausible characters, then feeds detected text to OCR and corrects the recognized words. The technique makes no assumptions about font, size, or orientation, and experimental results show encouraging recognition efficiency.
Topographic paper maps are a common support for ge- ographical information. In the field of document analysis of this kind of support, this paper proposes an automatic approach to extract and recognize toponyms. We present a technique based on image segmentation and connected component processing. Different filtering stages ensure the consistency of plausible characters and strings. Detected text areas are used to feed an OCR software and the recog- nized words are analyzed and corrected. The main advan- tage of our technique is that no assumption is made about the character font, size or orientation. Experimental results obtained are encouraging in term of recognition efficiency.
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Melvyn H. Schreiber · Investigative Radiology · 1992 · 94 citations
A robust algorithm for text detection in images
Julinda Gllavata, Ralph Ewerth, Bernd Freisleben · 2004 · 83 citations