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On the Development of an OCR System for Indian Postal Automation

Om On the Development of an OCR System for Indian Postal Automation

Various problems towards the development of Indian Postal Automation (IPA) system is discussed here. More specifically, in this endeavor, some of the tasks such as, statistical analysis of Indian postal documents, bi-lingual pin code digit recognition, script identification prior to city name recognition, and Dynamic Programming (DP) based city name recognition of Bangla script are the major contributions of this work. The feature sets considered  for the work consists of Structural and Statistical features, Normalized binary pixel images, Direction code based features, Gradient based features etc. For recognition, two categories of classifiers, viz., Multi Layer Perceptron (MLP) and Modified Quadratic Discriminant Function (MQDF) based classifiers have been selectively tested here and detailed results are presented.

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  • Språk:
  • Engelska
  • ISBN:
  • 9783844314038
  • Format:
  • Häftad
  • Sidor:
  • 148
  • Utgiven:
  • 17. mars 2011
  • Mått:
  • 152x229x9 mm.
  • Vikt:
  • 227 g.
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Leveranstid: 2-4 veckor
Förväntad leverans: 20. december 2024
Förlängd ångerrätt till 31. januari 2025

Beskrivning av On the Development of an OCR System for Indian Postal Automation

Various problems towards the development of Indian Postal Automation (IPA) system is discussed here. More specifically, in this endeavor, some of the tasks such as, statistical analysis of Indian postal documents, bi-lingual pin code digit recognition, script identification prior to city name recognition, and Dynamic Programming (DP) based city name recognition of Bangla script are the major contributions of this work. The feature sets considered  for the work consists of Structural and Statistical features, Normalized binary pixel images, Direction code based features, Gradient based features etc. For recognition, two categories of classifiers, viz., Multi Layer Perceptron (MLP) and Modified Quadratic Discriminant Function (MQDF) based classifiers have been selectively tested here and detailed results are presented.

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