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

Publication Links

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

IJACSA

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

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

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

Computing Conference

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

Intelligent Systems Conference (IntelliSys)

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

Future Technologies Conference (FTC)

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

DOI: 10.14569/IJACSA.2015.061139
PDF

A Multiple-Objects Recognition Method Based on Region Similarity Measures: Application to Roof Extraction from Orthophotoplans

Author 1: Abdellatif El Idrissi
Author 2: Youssef El Merabet
Author 3: Yassine Ruichek
Author 4: Raja Touahni
Author 5: Abderrahmane Sbihi
Author 6: Cyril Meurie
Author 7: Ahmed Moussa

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 6 Issue 11, 2015.

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

Abstract: In this paper, an efficient method for automatic and accurate detection of multiple objects from images using a region similarity measure is presented. This method involves the construction of two knowledge databases: The first one contains several distinctive textures of objects to be extracted. The second one is composed with textures representing background. Both databases are provided by some examples (training set) of images from which one wants to recognize objects. The proposed procedure starts by an initialization step during which the studied image is segmented into homogeneous regions. In order to separate the objects of interest from the image background, an evaluation of the similarity between the regions of the segmented image and those of the constructed knowledge databases is then performed. The proposed approach presents several advantages in terms of applicability, suitability and simplicity. Experimental results obtained from the method applied to extract building roofs from orthophotoplans prove its robustness and performance over popular methods like K Nearest Neighbours (KNN) and Support Vector Machine (SVM).

Keywords: Object recognition; Region Similarity Measure; Tex-ture; Feature extraction; Orthophotoplans

Abdellatif El Idrissi, Youssef El Merabet, Yassine Ruichek, Raja Touahni, Abderrahmane Sbihi, Cyril Meurie and Ahmed Moussa, “A Multiple-Objects Recognition Method Based on Region Similarity Measures: Application to Roof Extraction from Orthophotoplans” International Journal of Advanced Computer Science and Applications(IJACSA), 6(11), 2015. http://dx.doi.org/10.14569/IJACSA.2015.061139

@article{Idrissi2015,
title = {A Multiple-Objects Recognition Method Based on Region Similarity Measures: Application to Roof Extraction from Orthophotoplans},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.061139},
url = {http://dx.doi.org/10.14569/IJACSA.2015.061139},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {11},
author = {Abdellatif El Idrissi and Youssef El Merabet and Yassine Ruichek and Raja Touahni and Abderrahmane Sbihi and Cyril Meurie and Ahmed Moussa}
}



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.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
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

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