We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Reseach Article

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.

References
  1. Tripathy N. and Pal U. 2006,”Handwriting segmentation of constrained Oriya text”, Sadhna, Vol.31, Part 6, pp. 755-769.
  2. Graphology – Handwriting Analysis http://www.businessballs.com/graphologyhandwritinganalysis.htm.
  3. Lei Zhang, Fuzong Lin, Bo Zhang, “Support Vector Machine Learning for Image Retrivel”, Image Processing, IEEE 2001 International Conference, page(s): 721 - 724 vol.2.
  4. Hua Hu, Jing Ye, Chunlai Chai, “A Talent Classification Method Based on SVM”, International Symposium on Intelligent Ubiquitous Computing and Education 2009, Page(s): 160 – 163.
  5. Champa H. N., Dr. K. R. AnandaKumar, “Artificial Neural Network for Human Bahavior Prediction through Handwriting Analysis”, International Journal of Computer Applications (0975-8887) Volume 2 – No.2, May 2010.
  6. Ameur BENSEFIA, Ali NOSARY, Thierry PAQUET, Laurent HEUTTE, “Writer Identification By Writer’s Invariants”, Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR’02) 0-7695-1692-0/02 $17.00 © 2002 IEEE.
  7. S.H. Cha, S. Srihari, “Multiple Feature Integration for Writer Verification”, 7th International Workshop on Frontiers in Handwriting Recognition; IWFHR VII, Amsterdam, The Netherlands, pp 333-342, 2000.
  8. U.V. Marti, R. Messerli, H. Bunke, “Writer Identification Using Text Line Based Features”, Proc. ICDAR’01, Seattle (USA), pp 101-105, 2001.
  9. A. Srihari, S. Cha, H. Arora, S. Lee, “Individuality of Handwritig: A Validity Study”, Proc. ICDAR’01, Seattle (USA), pp 106-109, 2001.
  10. N Mogharreban, S Rahimi, M Sabharwal, “A Combined Crisp and Fuzzy Approach for Handwriting Analysis”, IEEE Annual Meeting of the Fuzzy Information, 2004, vol.1, pp. 351-356.
  11. Champa H N, K R AnandaKumar, “A Scientific Approach to Behavior Analysis through Handwriting Analysis”, National Conference on Research Trenda in Information Technology, S R K R Engineering College, Bhimavaram, Andhra Pradesh, 2008.
  12. Deodhare Dipti, Suri NNR Ranga, Amit R. 2005, “Preprocessing and Image Enhancement Algorithms for a Form-based Intelligent Character Recognition System”, International Journal of Computer Science and Application, Vol 2 No.2, pp. 131-144.
  13. Daekeun You and Gyeonghwan Kim, “An approach for locating segmentation points of handwritten digit strings using a neural network”, Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003).
  14. Champa H N, K R AnandaKumar, “ Writer’s Personality Prediction through letter „y‟ using Generalized Hough Transform(GHT) ”, 3rd International Conference on Information Processing, organized by the Society of Information Processing, Bangalore, Defence Institute of Advanced Technology and University Visveswaraya College of Engineering, Bangalore, 2009.
  15. Champa H N, K R AnandaKumar, “ Rule Based Approach for Personality Prediction Through Handwriting Analysis”, 2nd International Conference on Biomedical Informatics and Signal processing, organized by Sai‘s BioSciences Research Institute Pvt. Ltd., 2009.
Index Terms

Computer Science
Information Sciences

Keywords

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