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JSRI 2010, 6(2): 141-160 Back to browse issues page
Persian Handwriting Analysis Using Functional Principal Components
Yasaman Hosseinkashi *1, Khalil Shafie
1- , yhossein@uwaterloo.cam
Abstract:   (3083 Views)

Principal components analysis is a well-known statistical method in dealing with large dependent data sets. It is also used in functional data for both purposes of data reduction as well as variation representation. On the other hand "handwriting" is one of the objects, studied in various statistical fields like pattern recognition and shape analysis. Considering time as the argument, the handwriting would be an infinite dimensional data; a functional object. In this paper we try to use the functional principal components analysis (FPCA) to the Persian handwriting data, analyzing the word Mehr which is the Persian term for Love.

Keywords: Principal components analysis, functional data analysis, B-spline smoothing, on-line handwriting
Full-Text [PDF 547 kb]   (1545 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/01/19 | Accepted: 2016/01/19 | Published: 2016/01/19
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Hosseinkashi Y, Shafie K. Persian Handwriting Analysis Using Functional Principal Components. JSRI 2010; 6 (2) :141-160
URL: http://jsri.srtc.ac.ir/article-1-114-en.html

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Volume 6, Issue 2 (3-2010) Back to browse issues page
مجله‌ی پژوهش‌های آماری ایران Journal of Statistical Research of Iran JSRI
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