Presentation 2002/7/11
Learning Pseudo Bayes Discriminant Method Based on Utilizing Difference Distribution of Feature Vectors
Hiroaki TAKEBE, Koji KUROKAWA, Yutaka KATSUYAMA, Satoshi NAOI,
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Abstract(in English) We developed a learning pseudo Bayes discriminant method, that dynamically adapts a pseudo Bayes discriminant function to a font and image degradation condition present in a text. In this method, the characteristics of character pattern deformations are expressed as a statistic of a difference distribution, and information represented by the difference distribution is integrated into the pseudo Bayes discriminant function. The formulation of integrating the difference distribution into the pseudo Bayes discriminant function results in that a covariance matrix of each category is adjusted based on the difference distribution. We evaluated the proposed method on multi-font texts and degraded texts such as compressed color images and faxed copies. We found that the recognition accuracy of our method for the evaluated texts was much higher than that of conventional methods.
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Keyword(in English) Pseudo Bayes discriminant method / Difference distribution / Font / Degraded documents
Paper # MVE2002-31
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Committee MVE
Conference Date 2002/7/11(1days)
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Registration To Media Experience and Virtual Environment (MVE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Learning Pseudo Bayes Discriminant Method Based on Utilizing Difference Distribution of Feature Vectors
Sub Title (in English)
Keyword(1) Pseudo Bayes discriminant method
Keyword(2) Difference distribution
Keyword(3) Font
Keyword(4) Degraded documents
1st Author's Name Hiroaki TAKEBE
1st Author's Affiliation FUJITSU LABORATORIES LTD.()
2nd Author's Name Koji KUROKAWA
2nd Author's Affiliation FUJITSU LABORATORIES LTD.
3rd Author's Name Yutaka KATSUYAMA
3rd Author's Affiliation FUJITSU LABORATORIES LTD.
4th Author's Name Satoshi NAOI
4th Author's Affiliation FUJITSU LABORATORIES LTD.
Date 2002/7/11
Paper # MVE2002-31
Volume (vol) vol.102
Number (no) 219
Page pp.pp.-
#Pages 6
Date of Issue