IEEE Style Citation: Sushma Sugandhi, Vinita Patil, “Person Identification Based On Handwriting,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.186-189, 2019.
MLA Citation
MLA Style Citation: Sushma Sugandhi, Vinita Patil "Person Identification Based On Handwriting." International Journal of Computer Sciences and Engineering 7.7 (2019): 186-189.
APA Citation
APA Style Citation: Sushma Sugandhi, Vinita Patil, (2019). Person Identification Based On Handwriting. International Journal of Computer Sciences and Engineering, 7(7), 186-189.
BibTex Citation
BibTex Style Citation:
@article{Sugandhi_2019,
author = {Sushma Sugandhi, Vinita Patil},
title = {Person Identification Based On Handwriting},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2019},
volume = {7},
Issue = {7},
month = {7},
year = {2019},
issn = {2347-2693},
pages = {186-189},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4742},
doi = {https://doi.org/10.26438/ijcse/v7i7.186189}
publisher = {IJCSE, Indore, INDIA},
}
RIS Citation
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i7.186189}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4742
TI - Person Identification Based On Handwriting
T2 - International Journal of Computer Sciences and Engineering
AU - Sushma Sugandhi, Vinita Patil
PY - 2019
DA - 2019/07/31
PB - IJCSE, Indore, INDIA
SP - 186-189
IS - 7
VL - 7
SN - 2347-2693
ER -
VIEWS
PDF
XML
589
344 downloads
255 downloads
Abstract
This design, implementation, and evaluation of a research work for developing an automatic person identification system using hand written biometric. The developed automatic person identification system mainly used toolboxes provided by MATLAB environment. . In order to train and test the developed automatic person identification system, an in-house hand written database is created, which contains hand signatures of different persons . The collected hand data have gone through pre-processing steps such as producing a digitized version of the signatures using a scanner, converting input images type to a standard binary images type, cropping, normalizing images size, and reshaping in order to produce a ready-to-use hand signatures database for training and testing the automatic person identification system. Global features such as signature height, image area, pure width, and pure height are then selected to be used in the system. For features training and classification, the support vector machine(SVM) is used.
Key-Words / Index Term
SVM,handwritingrecognition,offline,online,static
References
[1].Naoya Wada ; “HMM Based Signature Identification System Robust to Changes of Signatures” with Time 2007 IEEE Workshop on Automatic Identification Advanced Technologies7-8 June 2007.
[2].A.A.M.Abushariah ; T.S. Gunawan ; J. Chebil ; M.A.M. Abushariah “Automatic person identification system using handwritten signatures” 2012 International Conference on Computer and Communication Engineering (ICCCE)3-5 July 2012.
[3].hifzan ahmed -shailjashukla ; hari mohan rai static “handwritten signature recognition using discrete random transform and combined projection based technique ”2014 fourth international conference on advanced computing & communication technologies.
[4].Parashuram- Chandrashekar Gudada Restoration of degraded “Kannada handwritten paper inscriptions (Hastaprati) using image enhancement techniques” 2017 International Conference on Computer Communication and Informatics (ICCCI).
[5]. Susana M. Vieira “Hybrid neural models for automatic handwritten digits recognition ”2018 International Joint Conference on Neural Networks (IJCNN).
VIEWS
PDF 
XML 
