A text reading algorithm for natural images

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摘要

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.

论文关键词:Text detection,Text recognition,Character recognition,Character segmentation,Natural images,Scene text detection

论文评审过程:Received 5 July 2012, Revised 30 October 2012, Accepted 22 January 2013, Available online 9 February 2013.

论文官网地址:https://doi.org/10.1016/j.imavis.2013.01.003