Open AccessWriter identification with n ‐tuple direction feature from contour
Author(s) -
Ghanbarian Alireza,
Ghiasi Golnaz,
Safabakhsh Reza,
Arastouie Narges
Publication year - 2020
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2018.6391
Subject(s) - histogram , feature (linguistics) , pattern recognition (psychology) , artificial intelligence , identification (biology) , tuple , computer science , feature extraction , computer vision , image (mathematics) , mathematics , linguistics , philosophy , botany , discrete mathematics , biology
This study introduces an effective solution for text‐independent writer identification by generalising contour‐hinge feature, which is called n ‐tuple direction feature. For extracting n ‐tuple direction feature, the authors first obtain all contours from connected components, then n + 1 points are considered on the contour with a certain distance apart, and next, the directions of the fragments connecting two successive points are computed. The n + 1 points move on the contour and the n ‐dimensional histogram of directions is computed. The proposed method is evaluated on large Farsi and English databases. A correct writer identification rate of 92.2% for English handwritings from 900 persons and 97.7% for Farsi handwritings from 600 persons are achieved. Comparison between the proposed method and other studies shows the promising performance and superiority of the proposed method.