A framework of artificial immune system in writer identification

Artificial Immune Systems (AIS) is an emerging computer science technique which is inspired from biological process and has a nonlinear classification property along with biological property such as Negative Selection (NS). AIS has been proved as one of the mechanism that has a good potential in sol...

Full description

Saved in:
Bibliographic Details
Main Authors: Muda, Azah Kamilah, Shamsuddin, Siti Mariyam
Format: Conference or Workshop Item
Language:English
Published: 2005
Subjects:
Online Access:http://eprints.utm.my/id/eprint/577/1/04.pdf
http://eprints.utm.my/id/eprint/577/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.577
record_format eprints
spelling my.utm.5772017-08-28T04:29:56Z http://eprints.utm.my/id/eprint/577/ A framework of artificial immune system in writer identification Muda, Azah Kamilah Shamsuddin, Siti Mariyam QA75 Electronic computers. Computer science Artificial Immune Systems (AIS) is an emerging computer science technique which is inspired from biological process and has a nonlinear classification property along with biological property such as Negative Selection (NS). AIS has been proved as one of the mechanism that has a good potential in solving complex problem such as pattern recognition. Meanwhile, handwritten writer identification is one of the most popular areas of research in pattern recognition due to its immense potential on commercial perspective. Due to the importance and increasing interest in bio-inspired computing, this paper proposed AIS framework for writer identification. However, early findings on data iris and pendigits show that the proposed framework is convincing with an accuracy of more than 80.0% with various matching techniques. 2005-09 Conference or Workshop Item NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/577/1/04.pdf Muda, Azah Kamilah and Shamsuddin, Siti Mariyam (2005) A framework of artificial immune system in writer identification. In: BIC`05, Puteri Pan Pacific Hotel, Johor Bahru.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Muda, Azah Kamilah
Shamsuddin, Siti Mariyam
A framework of artificial immune system in writer identification
description Artificial Immune Systems (AIS) is an emerging computer science technique which is inspired from biological process and has a nonlinear classification property along with biological property such as Negative Selection (NS). AIS has been proved as one of the mechanism that has a good potential in solving complex problem such as pattern recognition. Meanwhile, handwritten writer identification is one of the most popular areas of research in pattern recognition due to its immense potential on commercial perspective. Due to the importance and increasing interest in bio-inspired computing, this paper proposed AIS framework for writer identification. However, early findings on data iris and pendigits show that the proposed framework is convincing with an accuracy of more than 80.0% with various matching techniques.
format Conference or Workshop Item
author Muda, Azah Kamilah
Shamsuddin, Siti Mariyam
author_facet Muda, Azah Kamilah
Shamsuddin, Siti Mariyam
author_sort Muda, Azah Kamilah
title A framework of artificial immune system in writer identification
title_short A framework of artificial immune system in writer identification
title_full A framework of artificial immune system in writer identification
title_fullStr A framework of artificial immune system in writer identification
title_full_unstemmed A framework of artificial immune system in writer identification
title_sort framework of artificial immune system in writer identification
publishDate 2005
url http://eprints.utm.my/id/eprint/577/1/04.pdf
http://eprints.utm.my/id/eprint/577/
_version_ 1643643135331401728
score 13.2014675