A text reading algorithm for both natural and born-digital images
Identificadores
Enlace permanente (URI): http://hdl.handle.net/10017/43242DOI: 10.1016/j.imavis.2013.01.003
ISSN: 0262-8856
Editor
Elsevier
Fecha de publicación
2013-03-01Patrocinadores
Ministerio de Economía y Competitividad
Comunidad de Madrid
Cita bibliográfica
González, A. & Bergasa, L.M. 2013, "A text reading algorithm for natural images", Image and Vision Computing, vol. 31, no. 3, pp. 255-274.
Palabras clave
Text detection
Text recognition
Character recognition
Character segmentation
Natural images
Scene text detection
Proyectos
info:eu-repo/grantAgreement/MICINN//TRA2011-29001-C04-01
info:eu-repo/grantAgreement/CAM//S-0505%2FDPI%2F000176
Tipo de documento
info:eu-repo/semantics/article
Versión
info:eu-repo/semantics/acceptedVersion
Versión del editor
https://doi.org/10.1016/j.imavis.2013.01.003Derechos
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
© 2013 Elsevier
Derechos de acceso
info:eu-repo/semantics/openAccess
Resumen
Reading text in natural images has focused again the attention of many researchers during the last few years due to the increasing availability of cheap image-capturing devices in low-cost products like mobile phones. Therefore, as text can be found on any environment, the applicability of text-reading systems is really extensive. For this purpose, we present in this paper a robust method to read text in natural images. It is composed of two main separated stages. Firstly, text is located in the image using a set of simple and fast-to-compute features highly discriminative between character and non-character objects. They are based on geometric and gradient properties. The second part of the system carries out the recognition of the previously detected text. It uses gradient features to recognize single characters and Dynamic Programming (DP) to correct misspelled words. Experimental results obtained with different challenging datasets show that the proposed system exceeds state-of-the-art performance, both in terms of localization and recognition.
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