Automatic Classification of TV news Articles Based on Telop Character Recognition

5 Citations 27 References
  • ARIKI Y.
    Faculty of Science and Technology, Ryukoku University
  • KATAYAMA M.
    Faculty of Science and Technology, Ryukoku University
  • ISOZUMI S.
    Faculty of Science and Technology, Ryukoku University

Bibliographic Information

Other Title
  • テロップ文字認識に基づくTVニュース記事の自動分類

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Description

The purpose of this study is to develop a multi-media database system for TV news video data. TV news video data consist of speech, characters and images. In this study, telop are recognized and put on the news articles as indices for classification. At first, telop frames which include telop characters are detected and the telop characters are extracted and recognized. Through morphological analysis of the recognized telop characters, keywords are extracted which consist of more than two characters. Their keywords are used as indices to classify the TV news articles. We carried out the experiments to 30 days of NHK 5 minutes news and obtained 95.4% telop character extraction rate, 81.4% character recognition rate and 83.8% article classification rate.

Journal

  • IPSJ SIG Notes

    IPSJ SIG Notes 116 (2), 9-16, 1998-07-09

    Information Processing Society of Japan (IPSJ)

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Keywords

Details 詳細情報について

  • CRID
    1571135652199979904
  • NII Article ID
    110002930818
  • NII Book ID
    AN10112482
  • ISSN
    09196072
  • Text Lang
    ja
  • Data Source
    • CiNii Articles

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