Fast perspective recovery of text in natural scenes

  • Authors:

  • Carlos Merino-Gracia;Majid Mirmehdi;José Sigut;José L. González-Mora

  • Affiliations:

  • Neurochemistry and Neuroimaging Laboratory, University of La Laguna, Spain and Visual Information Laboratory, University of Bristol, United Kingdom;Visual Information Laboratory, University of Bristol, United Kingdom;Department of Systems Engineering and Control and Computer Architecture, University of La Laguna, Spain;Neurochemistry and Neuroimaging Laboratory, University of La Laguna, Spain

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2013

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Abstract

Cheap, ubiquitous, high-resolution digital cameras have led to opportunities that demand camera-based text understanding, such as wearable computing or assistive technology. Perspective distortion is one of the main challenges for text recognition in camera captured images since the camera may often not have a fronto-parallel view of the text. We present a method for perspective recovery of text in natural scenes, where text can appear as isolated words, short sentences or small paragraphs (as found on posters, billboards, shop and street signs etc.). It relies on the geometry of the characters themselves to estimate a rectifying homography for every line of text, irrespective of the view of the text over a large range of orientations. The horizontal perspective foreshortening is corrected by fitting two lines to the top and bottom of the text, while the vertical perspective foreshortening and shearing are estimated by performing a linear regression on the shear variation of the individual characters within the text line. The proposed method is efficient and fast. We present comparative results with improved recognition accuracy against the current state-of-the-art.