CEDAR

CEDAR’s CDROM-1 database contains handwritten words and ZIP Codes in high resolution grayscale (300 ppi 8-bit) as well as binary handwritten digits and alphanumeric characters (300 ppi 1-bit). This database is intended to encourage research in off-line handwriting recognition by providing access to handwriting samples digitized from envelopes in a post office.

Keywords for this software

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References in zbMATH (referenced in 6 articles )

Showing results 1 to 6 of 6.
Sorted by year (citations)

  1. Impedovo, D.; Pirlo, G.: Zoning methods for handwritten character recognition: A survey (2014) ioport
  2. Vamvakas, Georgios; Gatos, Basilis; Perantonis, Stavros J.: Handwritten character recognition through two-stage foreground sub-sampling (2010)
  3. Blumenstein, Michael; Liu, Xin Yu; Verma, Brijesh: An investigation of the modified direction feature for cursive character recognition (2007)
  4. Camastra, Francesco: A SVM-based cursive character recognizer (2007)
  5. Hanmandlu, M.; Murthy, O. V. Ramana: Fuzzy model based recognition of handwritten numerals (2007)
  6. Liu, Cheng-Lin; Nakashima, Kazuki; Sako, Hiroshi; Fujisawa, Hiromichi: Handwritten digit recognition: Benchmarking of state-of-the-art techniques. (2003)


Further publications can be found at: http://www.cedar.buffalo.edu/papers/publications.html