The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving
  • Editorial Board

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Computing Conference 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future of Information and Communication Conference (FICC) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Classification of Alzheimer Disease based on Normalized Hu Moment Invariants and Multiclassifier

Author 1: Arwa Mohammed Taqi
Author 2: Fadwa Al-Azzo
Author 3: Mariofanna Milanova

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.081102

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 11, 2017.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: There is a great benefit of Alzheimer disease (AD) classification for health care application. AD is the most common form of dementia. This paper presents a new methodology of invariant interest point descriptor for Alzheimer disease classification. The descriptor depends on the normalized Hu Moment Invariants (NHMI). The proposed approach deals with raw Magnetic Resonance Imaging (MRI) of Alzheimer disease. Seven Hu moments are computed for extracting images’ features. These moments are then normalized giving new more powerful features that highly improve the classification system performance. The moments are invariant which is the robustness point of Hu moments algorithm to extract features. The classification process is implemented using two different classifiers, K-Nearest Neighbors algorithm (KNN) and Linear Support Vector Machines (SVM). A comparison among their performances is investigated. The results are evaluated on Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The best classification accuracy is 91.4% for KNN classifier and 100% for SVM classifier.

Keywords: Alzheimer disease; machine learning; Hu moment invariants; SVM; K-Nearest Neighbors (KNN) classifier

Arwa Mohammed Taqi, Fadwa Al-Azzo and Mariofanna Milanova, “Classification of Alzheimer Disease based on Normalized Hu Moment Invariants and Multiclassifier” International Journal of Advanced Computer Science and Applications(IJACSA), 8(11), 2017. http://dx.doi.org/10.14569/IJACSA.2017.081102

@article{Taqi2017,
title = {Classification of Alzheimer Disease based on Normalized Hu Moment Invariants and Multiclassifier},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.081102},
url = {http://dx.doi.org/10.14569/IJACSA.2017.081102},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {11},
author = {Arwa Mohammed Taqi and Fadwa Al-Azzo and Mariofanna Milanova}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2021

29-30 April 2021

  • Virtual

Computing Conference 2021

15-16 July 2021

  • London, United Kingdom

IntelliSys 2021

2-3 September 2021

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2021

28-29 October 2021

  • Vancouver, Canada
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© 2018 The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org