Rotation Invariant Indexing For Image Using Zernike Moments and R–Tree
Abstract: The Zernike moment
algorithm and R-Tree algorithm are known as state of the art in the recognition
of images and in the multimedia database respectively. The methods of storing
the images and retrieving the similar images based on a query image automatically
are the problems in the image database. This paper proposes the method to
combine the Zernike moments algorithm and the R–tree algorithm in the image
database. The indices of images which are retrieved from the extraction process
using Zernike moments algorithm are used as the multidimensional indices to
recognize the images. The multidimensional indices of Zernike moments which are
stored in the R–tree are compared to the magnitudes of Zernike moments of a
query image for searching the similar images. The result shows that the
combination of these algorithms can be used efficiently in the image database
because the recognition accuracy rate using Zernike moments algorithm is
95.20%.
Author: Saptadi Nugroho,
Darmawan Utomo
Journal Code: jptkomputergg110042
