RT info:eu-repo/semantics/article
T1 A text reading algorithm for both natural and born-digital images
A1 González Arroyo, Álvaro
A1 Bergasa Pascual, Luis Miguel
K1 Text detection
K1 Text recognition
K1 Character recognition
K1 Character segmentation
K1 Natural images
K1 Scene text detection
K1 Electrónica
K1 Electronics
AB 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.
PB Elsevier
SN 0262-8856
YR 2013
FD 2013-03-01
LK http://hdl.handle.net/10017/43242
UL http://hdl.handle.net/10017/43242
LA eng
NO Ministerio de Economía y Competitividad
DS MINDS@UW
RD 19-abr-2024