ANALYSIS OF PERSONAL INFORMATION IN HANDWRITTEN CHARACTERS, AND AUTOMATIC WRITER RECOGNITION USING A SPECTRAL RESOLUTION TECHNIQUE.

Takeshi Shakunaga, Hiroshi Kaneko, Eiji Yodogawa

Research output: Contribution to journalArticle

Abstract

This paper proposes application of a new spectral resolution technique of 2nd order statistics for the purpose of extracting personal information from handwritten characters. This resolution technique was formulated based on a textural analysis viewpoint, and put to use for automatic writer recognition. Three algorithms were developed for text-independent identification, text-dependent identification and text-dependent verification. Experiments with five characters regarding text-dependent writer identification show that the identification rate is 99. 979% for 30 persons. Moreover, in verification experiments, false acceptance was only 0. 0034% when false rejection was 5. 2% for 29 registrants and five characters.

Original languageEnglish
Pages (from-to)35-46
Number of pages12
JournalDenki Tsushin Kenkyujo kenkyu jitsuyoka hokoku
Volume34
Issue number1
Publication statusPublished - 1985
Externally publishedYes

ASJC Scopus subject areas

  • Engineering(all)

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