doi: 10.7763/IJMLC.2012.V2.211
Image Registration Based On a Novel Enhanced Scale Invariant Geometrical Feature
Ehsan Hossein KalatehJari
,
Mohammad Mehdi Hosseini ,
Abdorreza Alavi Gharahbagh
- department of electrical and computer engineering, Islamic azad university, shahrood branch, shahrood, Iran.
Abstract
Image registration can find similarities between one image and another one from the same scene taken by different angles. Registration is widely used in robot localization, remote sensing, medical imaging and etc. In this paper, a new method based on the image geometrical features has introduced by using two important characteristics of image scale and image rotation. Feature points of two images by SIFT algorithm has extracted. Then, an initial matching is estimated based on descriptor matrix of SIFT features with nearest neighbor (NN) criterion. The novel geometrical method is used for discarding incorrect matched points. Finally, the correct image is recognized by the number of matched points.
Keywords
- Nearest neighbor
- sift
- geometrical transform
- image registration
How to Cite
Ehsan Hossein KalatehJari, Mohammad Mehdi Hosseini, and Abdorreza Alavi Gharahbagh, "Image Registration Based On a Novel Enhanced Scale Invariant Geometrical Feature," International Journal of Machine Learning, vol. 2, no. 5, pp. 667-671, 2012. https://doi.org/10.7763/IJMLC.2012.V2.211
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).