Mosul University
  • Register
  • Login
  • العربیة

AL-Rafidain Journal of Computer Sciences and Mathematics

Notice

As part of Open Journals’ initiatives, we create website for scholarly open access journals. If you are responsible for this journal and would like to know more about how to use the editorial system, please visit our website at https://ejournalplus.com or
send us an email to info@ejournalplus.com

We will contact you soon

  1. Home
  2. Volume 14, Issue 2
  3. Authors

Current Issue

By Issue

By Subject

Keyword Index

Author Index

Indexing Databases XML

About Journal

Aims and Scope

Editorial Board

Editorial Staff

Publication Ethics

Indexing and Abstracting

Related Links

Peer Review Process

News

Palm Print Features for Personal Authentication Based On Seven Moments

    Khaleda B. Ali Khalil I. Alsaif

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 2, Pages 63-74
10.33899/csmj.2020.167339

  • Show Article
  • Download
  • Cite
  • Statistics
  • Share

Abstract

Biometric images are considered as one of the major coefficients in the field of personal authentication. One of the main approaches for personal identification is based on palm print. So studying the features extracted from palm print image adopted to get high efficient system for any recognition systems. In this research two major phases are hold on, in the first phase a database was built for 100 persons by acquiring four images for both hands (4 for left hand and 4 for right hand), then processed to extract ROI (region of interest) by looking for the palm centroid then a square area is fixed based on that centroid. The pre-process play an important step for stable features. Evaluation of the seven moments for each image (8 images) follow the preprocess then stored in the database file (so each person will have 56 values), this phase called personal database preparation. The second phase is the detection phase, which requires the same steps to get 56 values then go through the database looking for the closest person to the tested one. The system evaluation measured by statistical metrics which show good result goes up to 95.7% when applied on 50 persons with different conditions. Also the effect of ROI dimension with individual hands and integrated both of them studied, and the recommended dimension is 192*192.
Keywords:
    image processing personal authentication invariant moments palmplrint features features extraction
Main Subjects:
  • Computer Science
  • Image Processing, Computer Vision, Pattern Recognition & Graphics
  • PDF (777 K)
  • XML
(2020). Palm Print Features for Personal Authentication Based On Seven Moments. AL-Rafidain Journal of Computer Sciences and Mathematics, 14(2), 63-74. doi: 10.33899/csmj.2020.167339
Khaleda B. Ali; Khalil I. Alsaif. "Palm Print Features for Personal Authentication Based On Seven Moments". AL-Rafidain Journal of Computer Sciences and Mathematics, 14, 2, 2020, 63-74. doi: 10.33899/csmj.2020.167339
(2020). 'Palm Print Features for Personal Authentication Based On Seven Moments', AL-Rafidain Journal of Computer Sciences and Mathematics, 14(2), pp. 63-74. doi: 10.33899/csmj.2020.167339
Palm Print Features for Personal Authentication Based On Seven Moments. AL-Rafidain Journal of Computer Sciences and Mathematics, 2020; 14(2): 63-74. doi: 10.33899/csmj.2020.167339
  • RIS
  • EndNote
  • BibTeX
  • APA
  • MLA
  • Harvard
  • Vancouver
  • Article View: 32
  • PDF Download: 28
  • LinkedIn
  • Twitter
  • Facebook
  • Google
  • Telegram
  • Home
  • Glossary
  • News
  • Aims and Scope
  • Privacy Policy
  • Sitemap
This journal is licensed under a Creative Commons Attribution 4.0 International (CC-BY 4.0)

Powered by eJournalPlus