JaLCDOI 10.18926/fest/11611
FullText URL 001_065_076.pdf
Author Kim, Hyun Bin| Tanaka, Yutaka|
Abstract Partial least squares linear discriminant function (PLSD) as well as ordinary linear discriminant function (LDF) are used in pattern recognition analysis of writer identification based on are patterns extracted from the writings written with Hangul letters by 20 Koreans. Also a simulation study is performed using the Monte Carlo method to compare the performances of PLSD and LDF. PLSD showed remarkably better performance than LDF in the Monte Calro study and slightly better performance in the analysis of the real pattern recognition data.
Keywords Writer identification Arc patterns Linear discriminant function Partial least squares
Publication Title 岡山大学環境理工学部研究報告
Published Date 1996-03
Volume volume1
Issue issue1
Start Page 65
End Page 76
ISSN 1341-9099
language 英語
File Version publisher
NAID 120002314147