A method for document zone content classification

Yalin Wang, Ihsin T. Phillips, Robert M. Haralick

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper describes an algorithm to classify each given document zone into one of nine classes and provides a protocol for its performance evaluation. The classification scheme uses an optimized binary decision tree and Viterbi algorithm for HMM to find the optimal solution. Our algorithm was trained and tested on a total of 24,177 zones within the 1600 images from UWCDROM III database. Its accuracy rate is 98.45% with a mean false alarm rate of 0.50%.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
Pages196-199
Number of pages4
Volume16
Edition3
StatePublished - 2002
Externally publishedYes

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture

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