Iraqi Journal for Electrical and Electronic Engineering
Login
Iraqi Journal for Electrical and Electronic Engineering
  • Home
  • Articles & Issues
    • Latest Issue
    • All Issues
  • Authors
    • Submit Manuscript
    • Guide for Authors
    • Authorship
    • Article Processing Charges (APC)
    • Proofreading Service
  • Reviewers
    • Guide for Reviewers
    • Become a Reviewer
  • About
    • About Journal
    • Aims and Scope
    • Editorial Team
    • Journal Insights
    • Peer Review Process
    • Publication Ethics
    • Plagiarism
    • Allegations of Misconduct
    • Appeals and Complaints
    • Corrections and Withdrawals
    • Open Access
    • Archiving Policy
    • Abstracting and indexing
    • Announcements
    • Contact

Search Results for discrimination-algorithm

Article
New Architectures and Algorithm for Optical Pattern Recognition using Joint Transform Correlation Technique

Prof. Dr. R. S. Fyath, Kh. N. Darraj

Pages: 33-50

PDF Full Text
Abstract

Recently, there is increasing interest in using joint transform correlation (JTC) technique for optical pattern recognition. In this technique, the target and reference images are jointed together in the input plane and no matched filter is required. In this paper, the JTC is investigated using simulation technique. A new discrimination decision algorithm is proposed to recognize the correlation output for different object shapes (dissimilar shapes). Also, new architectures are proposed to overcome the main problems of the conventional JTC.

1 - 1 of 1 items

Search Parameters

Journal Logo
Iraqi Journal for Electrical and Electronic Engineering

College of Engineering, University of Basrah

  • Copyright Policy
  • Terms & Conditions
  • Privacy Policy
  • Accessibility
  • Cookie Settings
Licensing & Open Access

CC BY 4.0 Logo Licensed under CC-BY-4.0

This journal provides immediate open access to its content.

Editorial Manager Logo Elsevier Logo

Peer-review powered by Elsevier’s Editorial Manager®

Copyright © 2025 College of Engineering, University of Basrah. All rights reserved, including those for text and data mining, AI training, and similar technologies.