Proceeding of the Electrical Engineering Computer Science and Informatics
Vol 2: EECSI 2015

Identification of Speed and Unique Letter of Handwriting Using Wavelet and Neural Networks

Esmeralda Contessa Djamal (Universitas Jenderal Achmad Yani)



Article Info

Publish Date
25 Sep 2017

Abstract

Handwriting  stroke  reflects  the  personality  and emotional    condition.    Graphology    is    scientific    method    to evaluation  personality  through  handwriting.  There  are  many features  in  graphology  to  identify  personality.  Several  previous researches  used  page  margins,  spacing,  baseline,  vertical  zone, font  size,  and  the  type  of  unique  letter  t.  Other  research  also identify the personality of signatures. This research uses feature writing  speed  and  the  type  of  letters  a,  d,  i  m,  and  t  to  identify personalities   using   structural   analysis   and   artificial   neural networks.  To  improve  accuracy,  image  writing  extracted  using wavelet transform. The system is built with the approach of the structure  and  symbol  has  been  implemented  in  software.  The results show a unique type of letter recognition by 74%, and the speed  feature  by  60%  recognition.  Variations  training  data greatly affect recognition results.

Copyrights © 2015






Journal Info

Abbrev

EECSI

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, ...