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Article:Handwriting Analysis based on Segmentation Method for Prediction of Human Personality using Support Vector Machine

by Shitala Prasad, Vivek Kumar Singh, Akshay Sapre
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 8 - Number 12
Year of Publication: 2010
Authors: Shitala Prasad, Vivek Kumar Singh, Akshay Sapre
10.5120/1256-1758

Shitala Prasad, Vivek Kumar Singh, Akshay Sapre . Article:Handwriting Analysis based on Segmentation Method for Prediction of Human Personality using Support Vector Machine. International Journal of Computer Applications. 8, 12 ( October 2010), 25-29. DOI=10.5120/1256-1758

@article{ 10.5120/1256-1758,
author = { Shitala Prasad, Vivek Kumar Singh, Akshay Sapre },
title = { Article:Handwriting Analysis based on Segmentation Method for Prediction of Human Personality using Support Vector Machine },
journal = { International Journal of Computer Applications },
issue_date = { October 2010 },
volume = { 8 },
number = { 12 },
month = { October },
year = { 2010 },
issn = { 0975-8887 },
pages = { 25-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume8/number12/1256-1758/ },
doi = { 10.5120/1256-1758 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:57:12.641489+05:30
%A Shitala Prasad
%A Vivek Kumar Singh
%A Akshay Sapre
%T Article:Handwriting Analysis based on Segmentation Method for Prediction of Human Personality using Support Vector Machine
%J International Journal of Computer Applications
%@ 0975-8887
%V 8
%N 12
%P 25-29
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Handwriting analysis is a method to predict personality of an author and to better understand the writer. Allograph and allograph combination analysis is a scientific method of writer identification and evaluating the behavior. To make this computerized we considered six main different types of features: (i) size of letters, (ii) slant of letters and words, (iii) baseline, (iv) pen pressure, (v) spacing between letters and (vi) spacing between words in a document to identify the personality of the writer. Segmentation is used to calculate the features from digital handwriting and is trained to SVM which outputs the behavior of the writer. For this experiment 100 different writers were used for different handwriting data samples. The proposed method gives about 94% of accuracy rate with RBF kernel. In this paper an automatic method has been proposed to predict the psychological personality of the writer. The system performance is measured under two different conditions with the same sample.

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Index Terms

Computer Science
Information Sciences

Keywords

Image processing Segmentation Graphology Handwriting Analysis Support Vector Machine Personality Traits Human Behavior Analysis Psychology