Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/6663
Title: Handwritten character skeletonisation for forensic document analysis
Contributor(s): Pervouchine, Vladimir (author); Leedham, Graham  (author); Melikhov, Konstantin (author)
Publication Date: 2005
DOI: 10.1145/1066677.1066850
Handle Link: https://hdl.handle.net/1959.11/6663
Abstract: A new method of skeletonisation (stroke extraction) of handwritten character images is presented. The method has been designed to extract the skeleton which is very close to human perception of the original pen tip trajectory. The need in such skeletonisation arises from feature extraction algorithms which are sensitive to inaccuracies in positions of skeleton curves. One class of such algorithms are those for extraction of features used in forensic analysis of handwriting. The skeleton is constructed in three steps directly from the grayscale image and is represented as a set of curves, which, in turn, are represented as cubic B-splines. Such representation also eases feature extraction. Experiments have been performed on 150 images of grapheme "th" written by different writers. The assessment of the skeletonisation results are presented.
Publication Type: Conference Publication
Conference Details: SAC 2005: 20th Annual ACM Symposium on Applied Computing, Santa Fe, New Mexico, 13th - 17th March, 2005
Source of Publication: Proceedings of the 2005 ACM Symposium on Applied Computing, v.1, p. 754-758
Publisher: Association for Computing Machinery (ACM)
Place of Publication: New York, United States of America
Fields of Research (FoR) 2008: 080104 Computer Vision
080106 Image Processing
Socio-Economic Objective (SEO) 2008: 810107 National Security
890299 Computer Software and Services not elsewhere classified
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Appears in Collections:Conference Publication
School of Science and Technology

Files in This Item:
3 files
File Description SizeFormat 
Show full item record

SCOPUSTM   
Citations

25
checked on Dec 7, 2024

Page view(s)

998
checked on Mar 8, 2023
Google Media

Google ScholarTM

Check

Altmetric


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.