IMAGE MATCHING IN JAVA
Fabien Julliard 



Introduction
We developed a new algorithm that matches two images: the source image and the target image. This algorithm is based on one elastic geometric transformation, which is applied on the source image.


Realization of the Elastic Transformation The
elastic transformation is done by some characteristic geometric coordinates
(landmarks), positioned by the user on each image, give the transformation.
Each landmark, on the source image, has only one corresponding landmark
on the target one. To find a correct elastic transformation, one constrain
is imposed: the coordinates of positioned landmarks on the target image
and the coordinates of landmarks on source image, after the process transform,
must be equal. This elastic transformation is the association between two
other transformations: the first is the affine transformation and the second
is one transformation based on residues interpolation. The difference between
the position of each landmark on target image and the position of the corresponding
landmark on source image, after process affine transform, is called residue.


Results The
geometric interpolation is implemented with three different degrees of
Bsplines: linear, quadratic and cubic. To set the fineness of the elastic
transformation (choice between a global or a local transformation), we
use a different number of intervals (higher number of intervals, more local
transformation).




Example of application of the elastic geometric transformation (Morphing):

