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Machine-Printed Character Recognition

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Handbook of Document Image Processing and Recognition

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Abstract

This chapter reviews salient advances in techniques for machine-printed character recognition. Section “Overview” provides a historical perspective (The description of the historical evolution of OCR is based upon the Wikipedia entry for this topic: http://en.wikipedia.org/wiki/Optical_character_recognition. The reader is referred to that page for a more detailed review) on how OCR techniques have evolved from the earliest stage (mechanical device) to special-purpose reading machines and to personal computer software. Section “Summary of the State-of-the-Art” summarizes the state of the art in machine-printed character recognition. Sections “Segmentation and Preprocessing”, “Isolated Character Recognition”, and “Word Recognition” describe core technologies including binarization, document image preprocessing, page segmentation, feature extraction, character classification, and language modeling that have been developed for modern character recognition systems. Section “Systems and Applications” introduces available machine-printed OCR systems and applications.

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Author information

Authors and Affiliations

  1. Raytheon BBN Technologies, Cambridge, MA, USA

    Huaigu Cao

  2. Information Sciences Institute, University of Southern California, Marina Del Rey, CA, USA

    Prem Natarajan

Authors
  1. Huaigu Cao
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  2. Prem Natarajan
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Corresponding author

Correspondence to Huaigu Cao .

Editor information

Editors and Affiliations

  1. University of Maryland, College Park, MD, USA

    David Doermann

  2. Université de Lorraine, Nancy, France

    Karl Tombre

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Cao, H., Natarajan, P. (2014). Machine-Printed Character Recognition. In: Doermann, D., Tombre, K. (eds) Handbook of Document Image Processing and Recognition. Springer, London. https://doi.org/10.1007/978-0-85729-859-1_44

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