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Individual English Handwriting Synthesis

by Riazat Ryan, Md. Haider Ali Kazal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 154 - Number 7
Year of Publication: 2016
Authors: Riazat Ryan, Md. Haider Ali Kazal
10.5120/ijca2016912189

Riazat Ryan, Md. Haider Ali Kazal . Individual English Handwriting Synthesis. International Journal of Computer Applications. 154, 7 ( Nov 2016), 7-11. DOI=10.5120/ijca2016912189

@article{ 10.5120/ijca2016912189,
author = { Riazat Ryan, Md. Haider Ali Kazal },
title = { Individual English Handwriting Synthesis },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2016 },
volume = { 154 },
number = { 7 },
month = { Nov },
year = { 2016 },
issn = { 0975-8887 },
pages = { 7-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume154/number7/26501-2016912189/ },
doi = { 10.5120/ijca2016912189 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:59:35.232406+05:30
%A Riazat Ryan
%A Md. Haider Ali Kazal
%T Individual English Handwriting Synthesis
%J International Journal of Computer Applications
%@ 0975-8887
%V 154
%N 7
%P 7-11
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Handwriting is considered as an input method through pen-based or touch-based mean. Consequently, it is an unique feature preserving users’ individuality. Since, it is becoming more lively aspect of user interaction, it is a very facile and more theoretical measure to reproduce an individual’s cursive and noncursive English handwriting from ASCII transcription. Special input arrangement is designed to collect user’s natural handwriting. Then, the system depicts the individuality features and characteristics of anyone’s handwriting that machine learns afterwards. And at last, at a given set of instructions, for any set of ASCII value, user natural handwriting is synthesized hierarchically.

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Index Terms

Computer Science
Information Sciences

Keywords

Control point Glyphs Stroke Ligature Bezier Curve 1-D Gabor Filter Slant Pressure Semi Supervised Machine Learning

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