Improved random forest for feature selection in writer identification

• Main Author: Sukor, Nooraziera Akmal
• Format: Thesis
• Language: English; English
• Published: 2015
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utem.edu.my/id/eprint/16842/1/Improved%20Random%20Forest%20For%20Feature%20Selection%20In%20Writer%20Identification.pdf; http://eprints.utem.edu.my/id/eprint/16842/2/Improved%20random%20forest%20for%20feature%20selection%20in%20writer%20identification.pdf; http://eprints.utem.edu.my/id/eprint/16842/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96166
• Institution: Universiti Teknikal Malaysia Melaka

Writer Identification (WI) is a process to determine the writer of a given handwriting sample. A handwriting sample consists of various types of features. These features are unique due to the writer’s characteristics and individuality, which challenges the identification process. Some features do no...