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Reseach Article

Image Mosaicing based on Neural Networks

by Tamer A. A. Alzohairy, Emad El-Dein H. A. Masameer, Mahmoud S. Sayed
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 1
Year of Publication: 2016
Authors: Tamer A. A. Alzohairy, Emad El-Dein H. A. Masameer, Mahmoud S. Sayed

Tamer A. A. Alzohairy, Emad El-Dein H. A. Masameer, Mahmoud S. Sayed . Image Mosaicing based on Neural Networks. International Journal of Computer Applications. 136, 1 ( February 2016), 25-31. DOI=10.5120/ijca2016908338

@article{ 10.5120/ijca2016908338,
author = { Tamer A. A. Alzohairy, Emad El-Dein H. A. Masameer, Mahmoud S. Sayed },
title = { Image Mosaicing based on Neural Networks },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 1 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 25-31 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2016908338 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:35:52.346750+05:30
%A Tamer A. A. Alzohairy
%A Emad El-Dein H. A. Masameer
%A Mahmoud S. Sayed
%T Image Mosaicing based on Neural Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 1
%P 25-31
%D 2016
%I Foundation of Computer Science (FCS), NY, USA

The main concept behind image mosaic is image registration. In image mosaicing several overlapping images are assembled in order to constitute one panoramic image. In this paper a new feature-based approach will be presented for automated image to image registration and mosaicing. The proposed method is implemented on real complex images. The proposed method is based on five main steps. First, the Harris algorithm is used to extract the feature points in the reference and sensed images. Second, feature matching is established using the Euclidean distance of the signature vectors obtained using pulse coupled neural network (PCNN). Third, transformation parameters are obtained using the least-square rule based on general affine transformation. Fourth, the image resampling and transformation are performed using bilinear interpolation to get the registered image. Finally, the mosaicing image is obtained. Experimental results show that the proposed algorithm shows excellent results when applied and tested on real complex images.

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Index Terms

Computer Science
Information Sciences


Registration Mosaicing Reference image Sensed image Affine transformation Pulse Coupled Neural Network (PCNN) and blending.