Automatic Feature Extraction and Text Recognition From Scanned Topographic Maps
Identifieur interne : 000573 ( Main/Exploration ); précédent : 000572; suivant : 000574Automatic Feature Extraction and Text Recognition From Scanned Topographic Maps
Auteurs : Aria Pezeshk [États-Unis] ; Richard L. Tutwiler [États-Unis]Source :
- IEEE transactions on geoscience and remote sensing [ 0196-2892 ] ; 2011.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
A system for automatic extraction of various feature layers and recognition of the text content of scanned topographic maps is presented here. Linear features which are often intersecting with the text are first extracted using a novel line representation method and a set of directional morphological operations. Other graphical objects are then removed in several stages to obtain a text-only image. A custom defect model is subsequently used to create an artificial training set for a Hidden Markov Model-based character recognition engine. Finally, the recovered text is recognized using this multifont segmentation-free optical character recognition (OCR). Extensive testing is conducted to assess the performance of different stages of the proposed system. Furthermore, our custom OCR is shown to achieve a 94% recognition rate for the extracted text, thereby outperforming a commercial OCR used as a benchmark.
Affiliations:
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Le document en format XML
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Tutwiler</name><affiliation wicri:level="4"><inist:fA14 i1="01"><s1>Applied Research Laboratory, The Pennsylvania State University</s1><s2>University Park, PA 16804</s2><s3>USA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ></inist:fA14><country>États-Unis</country><placeName><region type="state">Pennsylvanie</region><settlement type="city">University Park (Pennsylvanie)</settlement></placeName><orgName type="university">Université d'État de Pennsylvanie</orgName></affiliation></author></analytic><series><title level="j" type="main">IEEE transactions on geoscience and remote sensing</title><title level="j" type="abbreviated">IEEE trans. geosci. remote sens.</title><idno type="ISSN">0196-2892</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">IEEE transactions on geoscience and remote sensing</title><title level="j" type="abbreviated">IEEE trans. geosci. remote sens.</title><idno type="ISSN">0196-2892</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>extraction</term><term>models</term><term>morphology</term><term>performances</term><term>segmentation</term><term>testing</term><term>topographic maps</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Extraction</term><term>Carte topographique</term><term>Modèle</term><term>Segmentation</term><term>Expérimentation</term><term>Performance</term><term>Morphologie</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">A system for automatic extraction of various feature layers and recognition of the text content of scanned topographic maps is presented here. Linear features which are often intersecting with the text are first extracted using a novel line representation method and a set of directional morphological operations. Other graphical objects are then removed in several stages to obtain a text-only image. A custom defect model is subsequently used to create an artificial training set for a Hidden Markov Model-based character recognition engine. Finally, the recovered text is recognized using this multifont segmentation-free optical character recognition (OCR). Extensive testing is conducted to assess the performance of different stages of the proposed system. Furthermore, our custom OCR is shown to achieve a 94% recognition rate for the extracted text, thereby outperforming a commercial OCR used as a benchmark.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Pennsylvanie</li></region><settlement><li>University Park (Pennsylvanie)</li></settlement><orgName><li>Université d'État de Pennsylvanie</li></orgName></list><tree><country name="États-Unis"><region name="Pennsylvanie"><name sortKey="Pezeshk, Aria" sort="Pezeshk, Aria" uniqKey="Pezeshk A" first="Aria" last="Pezeshk">Aria Pezeshk</name></region><name sortKey="Tutwiler, Richard L" sort="Tutwiler, Richard L" uniqKey="Tutwiler R" first="Richard L." last="Tutwiler">Richard L. Tutwiler</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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