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Rectification and recognition of text in 3-D scenes

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International Journal of Document Analysis and Recognition (IJDAR) Aims and scope Submit manuscript

Abstract.

Real-world text on street signs, nameplates, etc. often lies in an oblique plane and hence cannot be recognized by traditional OCR systems due to perspective distortion. Furthermore, such text often comprises only one or two lines, preventing the use of existing perspective rectification methods that were primarily designed for images of document pages. We propose an approach that reliably rectifies and subsequently recognizes individual lines of text. Our system, which includes novel algorithms for extraction of text from real-world scenery, perspective rectification, and binarization, has been rigorously tested on still imagery as well as on MPEG-2 video clips in real time.

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Authors and Affiliations

  1. SRI International, 333 Ravenswood Avenue, CA 94025, Menlo Park, USA

    Gregory K. Myers, Robert C. Bolles, Quang-Tuan Luong, James A. Herson & Hrishikesh B. Aradhye

Authors
  1. Gregory K. Myers
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  2. Robert C. Bolles
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  3. Quang-Tuan Luong
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  4. James A. Herson
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  5. Hrishikesh B. Aradhye
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Corresponding author

Correspondence to Gregory K. Myers.

Additional information

Received: 15 December 2003, Published online: 14 December 2004

Gregory K. Myers: Correspondence to

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Myers, G.K., Bolles, R.C., Luong, QT. et al. Rectification and recognition of text in 3-D scenes. IJDAR 7, 147–158 (2005). https://doi.org/10.1007/s10032-004-0133-4

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  • DOI: https://doi.org/10.1007/s10032-004-0133-4

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