岡山大学環境理工学部研究報告 ISSN 2187-6940
Published by Faculty of Environmental Science and Technology, Okayama University

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Application of Partial Least Squares Linear Discriminant Function to Writer Identification in Pattern Recognition Analysis

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
ISSN
1341-9099
NCID
AN10529213