• Treffer 26 von 1884
Zurück zur Trefferliste

A framework for improved video text detection and recognition

  • Text displayed in a video is an essential part for the high-level semantic information of the video content. Therefore, video text can be used as a valuable source for automated video indexing in digital video libraries. In this paper, we propose a workflow for video text detection and recognition. In the text detection stage, we have developed a fast localization-verification scheme, in which an edge-based multi-scale text detector first identifies potential text candidates with high recall rate. Then, detected candidate text lines are refined by using an image entropy-based filter. Finally, Stroke Width Transform (SWT)- and Support Vector Machine (SVM)-based verification procedures are applied to eliminate the false alarms. For text recognition, we have developed a novel skeleton-based binarization method in order to separate text from complex backgrounds to make it processible for standard OCR (Optical Character Recognition) software. Operability and accuracy of proposed text detection and binarization methods have been evaluatedText displayed in a video is an essential part for the high-level semantic information of the video content. Therefore, video text can be used as a valuable source for automated video indexing in digital video libraries. In this paper, we propose a workflow for video text detection and recognition. In the text detection stage, we have developed a fast localization-verification scheme, in which an edge-based multi-scale text detector first identifies potential text candidates with high recall rate. Then, detected candidate text lines are refined by using an image entropy-based filter. Finally, Stroke Width Transform (SWT)- and Support Vector Machine (SVM)-based verification procedures are applied to eliminate the false alarms. For text recognition, we have developed a novel skeleton-based binarization method in order to separate text from complex backgrounds to make it processible for standard OCR (Optical Character Recognition) software. Operability and accuracy of proposed text detection and binarization methods have been evaluated by using publicly available test data sets.zeige mehrzeige weniger

Metadaten exportieren

Weitere Dienste

Suche bei Google Scholar Statistik - Anzahl der Zugriffe auf das Dokument
Metadaten
Verfasserangaben:Haojin YangGND, Bernhard Quehl, Harald SackORCiDGND
DOI:https://doi.org/10.1007/s11042-012-1250-6
ISSN:1380-7501
ISSN:1573-7721
Titel des übergeordneten Werks (Englisch):Multimedia tools and applications : an international journal
Verlag:Springer
Verlagsort:Dordrecht
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Jahr der Erstveröffentlichung:2014
Erscheinungsjahr:2014
Datum der Freischaltung:27.03.2017
Freies Schlagwort / Tag:Multimedia retrieval; Video OCR; Video indexing
Band:69
Ausgabe:1
Seitenanzahl:29
Erste Seite:217
Letzte Seite:245
Fördernde Institution:Mediaglobe project; German Federal Ministry of Economics and Technology on the basis of a decision by the German Bundestag [FKZ: 01MQ09031]
Organisationseinheiten:An-Institute / Hasso-Plattner-Institut für Digital Engineering gGmbH
Peer Review:Referiert
Verstanden ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.