Application of Partial Least Squares Linear Discriminant Function to Writer Identification in Pattern Recognition Analysis
نویسندگان
چکیده
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 arc 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.
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